2023 Volume 3
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Progress and prospects in crowd safety evacuation research in China

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  • China has a population of 1.4 billion, ranking first in the world. With the increase in China's economic development and population, the construction of various types of buildings in China is also increasing, and associated safety hazards are gradually increasing. Therefore, it is necessary to study the safe evacuation of people inside and outside the building in emergency situations. In recent years, some scholars have used the traditional statistical method of literature review to analyze the research frontiers in the field of safety evacuation, but few scholars have used bibliometric methods to analyze and review the current situation of research in this field. Therefore, this paper adopts the analysis method combining bibliometrics and traditional literature review to summarize the research status of crowd evacuation published by Chinese scholars in the Web of Science core database, and uses VOSviewer to analyze the authors, institutions, and keywords of the literature search results, so as to identify their research hotspots. The results show that the last three years have been the peak period of crowd evacuation studies, with many disciplines involved in this field and they are closely related, led by the number of papers related to architecture. Simulation, model, behavior, among others, have been the most used keywords in this research field, and the research on path planning and exit selection behavior has also increased significantly. According to the keyword analysis, three hot spots of safety evacuation research, namely large-scale group evacuation, evacuation path planning and evacuation exit selection are analyzed in detail.
  • Columnar cacti are plants of the Cactaceae family distributed across arid and semi-arid regions of America, with ecological, economic, and cultural value[1]. One trait that makes it possible for the columnar cactus to survive in the desert ecosystem is its thick epidermis covered by a hydrophobic cuticle, which limits water loss in dry conditions[1]. The cuticle is the external layer that covers the non-woody aerial organs of land plants. The careful control of cuticle biosynthesis could produce drought stress tolerance in relevant crop plants[2]. In fleshy fruits, the cuticle maintains adequate water content during fruit development on the plant and reduces water loss in fruit during postharvest[3]. Efforts to elucidate the molecular pathway of cuticle biosynthesis have been carried out for fleshy fruits such as tomato (Solanum lycopersicum)[4], apple (Malus domestica)[5], sweet cherry (Prunus avium)[6], mango (Mangifera indica)[7], and pear (Pyrus 'Yuluxiang')[8].

    The plant cuticle is formed by the two main layers cutin and cuticular waxes[3]. Cutin is composed mainly of oxygenated long-chain (LC) fatty acids (FA), which are synthesized by cytochrome p450 (CYP) enzymes. CYP family 86 subfamily A (CYP86A) enzymes carry out the terminal (ω) oxidation of LC-FA[9]. Then, CYP77A carries out the mid-chain oxidation to synthesize the main cutin monomers. In Arabidopsis, AtCYP77A4 and AtCYP77A6 carry out the synthesis of mid-chain epoxy and mid-chain dihydroxy LC-FA, respectively[10,11]. AtCYP77A6 is required for the cutin biosynthesis and the correct formation of floral surfaces[10]. The expression of CYP77A19 (KF410855) and CYP77A20 (KF410856) from potato (Solanum tuberosum) restored the petal cuticular impermeability in Arabidopsis null mutant cyp77a6-1, tentatively by the synthesis of cutin monomers[12]. In eggplant (Solanum torvum), the over-expression of StoCYP77A2 leads to resistance to Verticillium dahlia infection in tobacco plants[13]. Although the function of CYP77A2 in cutin biosynthesis has not yet been tested, gene expression analysis suggests that CaCYP77A2 (A0A1U8GYB0) could play a role in cutin biosynthesis during pepper fruit development[14].

    It has been hypothesized that the export of cuticle precursors is carried out by ATP binding cassette subfamily G (ABCG) transporters. ABCG11/WBC11, ABCG12, and ABCG13 are required for the load of cuticle lipids in Arabidopsis[1517], but ABCG13 function appears to be specific to the flower epidermis[18]. The overexpression of TsABCG11 (JQ389853) from Thellungiella salsugineum increases cuticle amounts and promotes tolerance to different abiotic stresses in Arabidopsis[19].

    Once exported, the cutin monomers are polymerized on the surface of epidermal cells. CD1 code for a Gly-Asp-Ser-Leu motif lipase/esterase (GDSL) from tomato required for the cutin formation through 2-mono(10,16-dihydroxyhexadecanoyl)glycerol esterification[20]. GDSL1 from tomato carries out the ester bond cross-links of cutin monomers located at the cuticle layers and is required for cuticle deposition in tomato fruits[21]. It has been shown that the transcription factor MIXTA-like reduces water loss in tomato fruits through the positive regulation of the expression of CYP77A2, ABCG11, and GDSL1[22]. Despite the relevant role of cuticles in maintaining cactus homeostasis in desert environments[1], the molecular mechanism of cuticle biosynthesis has yet to be described for cactus fruits.

    Stenocereus thurberi is a columnar cactus endemic from the Sonoran desert (Mexico), which produces an ovoid-globose fleshy fruit named sweet pitaya[23]. In its mature state, the pulp of sweet pitaya contains around 86% water with a high content of antioxidants and natural pigments such as betalains and phenolic compounds, which have nutraceutical and industrial relevance[23]. Due to the arid environment in which pitaya fruit grows, studying its molecular mechanism of cuticle biosynthesis can generate new insights into understanding species' adaptation mechanisms to arid environments. Nevertheless, sequences of transcripts from S. thurberi in public databases are scarce.

    RNA-sequencing technology (RNA-seq) allows the massive generation of almost all the transcripts from non-model plants, even if no complete assembled genome is available[24]. Recent advances in bioinformatic tools has improved our capacity to identify long non-coding RNA (lncRNA), which have been showed to play regulatory roles in relevant biological processes, such as the regulation of drought stress tolerance in plants[25], fruit development, and ripening[2629].

    In this study, RNA-seq data were obtained for the de novo assembly and characterization of the S. thurberi fruit peel transcriptome. As a first approach, three transcripts, StCYP77A, StABCG11, and StGDSL1, tentatively involved in cuticle biosynthesis, were identified and quantified during sweet pitaya fruit development. Due to no gene expression analysis having been carried out yet for S. thurberi, stably expressed constitutive genes were identified for the first time.

    Sweet pitaya fruits (S. thurberi) without physical damage were hand harvested from plants in a native conditions field located at Carbó, Sonora, México. They were collocated in a cooler containing dry ice and transported immediately to the laboratory. The superficial part of the peels (~1 mm deep) was removed carefully from the fruits using a scalpel. Peel samples from three fruits were pooled according to their tentative stage of development defined by their visual characteristics, frozen in liquid nitrogen, and pulverized to create a single biological replicate. Four samples belonging to four different plants were analyzed. All fruits harvested were close to the ripening stage. Samples named M1 and M2 were turning from green to ripe [~35−40 Days After Flowering (DAF)], whereas samples M3 and M4 were turning from ripe to overripe (~40−45 DAF).

    Total RNA was isolated from the peels through the Hot Borate method[30]. The concentration and purity of RNA were determined in a spectrophotometer Nanodrop 2000 (Thermo Fisher) by measuring the 260/280 and 260/230 absorbance ratios. RNA integrity was evaluated through electrophoresis in agarose gel 1% and a Bioanalyzer 2100 (Agilent). Pure RNA was sequenced in the paired-end mode in an Illumina NextSeq 500 platform at the University of Arizona Genetics Core Facility. Four RNA-seq libraries, each of them from each sample, were obtained, which include a total of 288,199,704 short reads with a length of 150 base pairs (bp). The resulting sequence data can be accessed at the Sequence Read Archive (SRA) repository of the NCBI through the BioProject ID PRJNA1030439. Libraries are named corresponding to the names of samples M1, M2, M3, and M4.

    FastQC software (www.bioinformatics.babraham.ac.uk/projects/fastqc) was used for short reads quality analysis. Short reads with poor quality were trimmed or eliminated by Trimmomatic (www.usadellab.org/cms/?page=trimmomatic) with a trailing and leading of 25, a sliding window of 4:25, and a minimum read length of 80 bp. A total of 243,194,888 reads with at least a 25 quality score on the Phred scale were used to carry out the de novo assembly by Trinity (https://github.com/trinityrnaseq/trinityrnaseq/wiki) with the following parameters: minimal k-mer coverage of 1, normalization of 50, and minimal transcript length of 200 bp.

    Removal of contaminating sequences and ribosomal RNA (rRNA) was carried out through SeqClean. To remove redundancy, transcripts with equal or more than 90% of identity were merged through CD-hit (www.bioinformatics.org/cd-hit/). Alignment and quantification in terms of transcripts per million (TPM) were carried out through Bowtie (https://bowtie-bio.sourceforge.net/index.shtml) and RSEM (https://github.com/deweylab/RSEM), respectively. Transcripts showing a low expression (TPM < 0.01) were discarded. Assembly quality was evaluated by calculating the parameters N50 value, mean transcript length, TransRate score, and completeness. The statistics of the transcriptome were determined by TrinityStats and TransRate (https://hibberdlab.com/transrate/). The transcriptome completeness was determined through a BLASTn alignment (E value < 1 × 10−3) by BUSCO (https://busco.ezlab.org/) against the database of conserved orthologous genes from Embryophyte.

    To predict the proteins tentatively coded in the S. thurberi transcriptome, the best homology match of the assembled transcripts was found by alignment to the Swiss-Prot, RefSeq, nr-NCBI, PlantTFDB, iTAK, TAIR, and ITAG databases using the BLAST algorithm with an E value threshold of 1 × 10−10 for the nr-NCBI database and of 1 × 10−5 for the others[3134]. An additional alignment was carried out to the protein databases of commercial fruits Persea americana, Prunus persica, Fragaria vesca, Citrus cinensis, and Vitis vinifera to proteins of the cactus Opuntia streptacantha, and the transcriptomes of the cactus Hylocereus polyrhizus, Pachycereus pringlei, and Selenicereus undatus. The list of all databases and the database websites of commercial fruits and cactus are provided in Supplementary Tables S1 & S2. The open reading frame (ORF) of the transcripts and the protein sequences tentative coded from the sweet pitaya transcriptome was predicted by TransDecoder (https://github.com/TransDecoder/TransDecoder/wiki), considering a minimal ORF length of 75 amino acids (aa). The search for protein domains was carried out by the InterPro database (www.ebi.ac.uk/interpro). Functional categorization was carried out by Blast2GO based on GO terms and KEGG metabolic pathways[35].

    LncRNA were identified based on the methods reported in previous studies[25,29,36]. Transcripts without homology to any protein from Swiss-Prot, RefSeq, nr-NCBI, PlantTFDB, iTAK, TAIR, ITAG, P. americana, P. persica, F. vesca, C. cinensis, V. vinifera, and O. streptacantha databases, without a predicted ORF longer than 75 aa, and without protein domains in the InterPro database were selected to identify tentative lncRNA.

    Transcripts coding for signal peptide or transmembrane helices were identified by SignalP (https://services.healthtech.dtu.dk/services/SignalP-6.0/) and TMHMM (https://services.healthtech.dtu.dk/services/TMHMM-2.0/), respectively, and discarded. Further, transcripts corresponding to other non-coding RNAs (ribosomal RNA and transfer RNA) were identified through Infernal by using the Rfam database[37] and discarded. The remaining transcripts were analyzed by CPC[38], and CPC2[39] to calculate their coding potential. Transcripts with a coding potential score lower than −1 for CPC and a coding probability lower than 0.1 for CPC2 were considered lncRNA. To characterize the identified lncRNA, the length and abundance of coding and lncRNA were calculated. Bowtie and RSEM were used to align and quantify raw counts, respectively. The edgeR package[40] was used to normalize raw count data in terms of counts per million (CPM) for both coding and lncRNA.

    To obtain the transcript's expression, the aligning of short reads and quantifying of transcripts were carried out through Bowtie and RSEM software, respectively. A differential expression analysis was carried out between the four libraries by edgeR package in R Studio. Only the transcripts with a count equal to or higher than 0.5 in at least one sample were retained for the analysis. Transcripts with log2 Fold Change (log2FC) between +1 and −1 and with a False Discovery Rate (FDR) lower than 0.05 were taken as not differentially expressed (NDE).

    For the identification of the tentative reference genes two strategies were carried out as described below: i) The NDE transcripts were aligned by BLASTn (E value < 1 × 10−5) to 43 constitutive genes previously reported in fruits from the cactus H. polyrhizus, S. monacanthus, and S. undatus[4143] to identify possible homologous constitutive genes in S. thurberi. Then, the homologous transcripts with the minimal coefficient of variation (CV) were selected; ii) For all the NDE transcripts, the percentile 95 value of the mean CPM and the percentile 5 value of the CV were used as filters to recover the most stably expressed transcripts, based on previous studies[44]. Finally, transcripts to be tested by quantitative reverse transcription polymerase chain reaction (qRT-PCR) were selected based on their homology and tentative biological function.

    The fruit harvesting was carried out as described above. Sweet pitaya fruit takes about 43 d to ripen, therefore, open flowers were tagged, and fruits with 10, 20, 30, 35, and 40 DAF were collected to cover the pitaya fruit development process (Supplementary Fig. S1). The superficial part of the peels (~1 mm deep) was removed carefully from the fruits using a scalpel. Peel samples from three fruits were pooled according to their stage of development defined by their DAF, frozen in liquid nitrogen, and pulverized to create a single biological replicate. One biological replicate consisted of peels from three fruits belonging to the same plant. Two to three biological replicates were evaluated for each developmental stage. Two technical replicates were analyzed for each biological replicate. RNA extraction, quantification, RNA purity, and RNA integrity analysis were carried out as described above.

    cDNA was synthesized from 100 ng of RNA by QuantiTect Reverse Transcription Kit (QIAGEN). Primers were designed using the PrimerQuest™, UNAFold, and OligoAnalyzer™ tools from Integrated DNA Technologies (www.idtdna.com/pages) and following the method proposed by Thornton & Basu[45]. Transcripts quantification was carried out in a QIAquant 96 5 plex according to the PowerUp™ SYBR™ Green Master Mix protocol (Applied Biosystems), with a first denaturation step for 2 min at 95 °C, followed by 40 cycles of denaturation step at 95 °C for 15 s, annealing and extension steps for 30 s at 60 °C.

    The Cycle threshold (Ct) values obtained from the qRT-PCR were analyzed through the algorithms BestKeeper, geNorm, NormFinder, and the delta Ct method[46]. RefFinder (www.ciidirsinaloa.com.mx/RefFinder-master/) was used to integrate the stability results and to find the most stable expressed transcripts in sweet pitaya fruit peel during development. The pairwise variation value (Vn/Vn + 1) was calculated through the geNorm algorithm in R Studio software[47].

    An alignment of 17 reported cuticle biosynthesis genes from model plants were carried out by BLASTx against the predicted proteins from sweet pitaya. Two additional alignments of 17 charaterized cuticle biosynthesis proteins from model plants against the transcripts and predicted proteins of sweet pitaya were carried out by tBLASTn and BLASTp, respectively. An E value threshold of 1 × 10−5 was used, and the unique best hits were recovered for all three alignments. The sequences of the 17 characterized cuticle biosynthesis genes and proteins from model plants are showed in Supplementary Table S3. The specific parameters and the unique best hits for all the alignments carried out are shown in Supplementary Tables S4S8.

    Cuticle biosynthesis-related transcripts tentatively coding for a cytochrome p450 family 77 subfamily A (CYP77A), a Gly-Asp-Ser-Leu motif lipase/esterase 1 (GDSL1), and an ATP binding cassette transporter subfamily G member 11 (ABCG11) were identified by best bi-directional hit according to the functional annotation described above. Protein-conserved domains, signal peptide, and transmembrane helix were predicted through InterProScan, SignalP 6.0, and TMHMM, respectively. Alignment of the protein sequences to tentative orthologous of other plant species was carried out by the MUSCLE algorithm[48]. A neighbor-joining (NJ) phylogenetic tree with a bootstrap of 1,000 replications was constructed by MEGA11[49].

    Fruit sampling, primer design, RNA extraction, cDNA synthesis, and transcript quantification were performed as described above. Relative expression was calculated according to the 2−ΔΔCᴛ method[50]. The sample corresponding to 10 DAF was used as the calibrator. The transcripts StEF1a, StTUA, StUBQ3, and StEF1a + StTUA were used as normalizer genes.

    Normality was assessed according to the Shapiro-Wilk test. Significant differences in the expression of the cuticle biosynthesis-related transcripts between fruit developmental stages were determined by one-way ANOVA based on a completely randomized sampling design and a Tukey honestly significant difference (HSD) test, considering a p-value < 0.05 as significant. Statistical analysis was carried out through the stats package in R Studio.

    RNA was extracted from the peels of ripe sweet pitaya fruits (S. thurberi) from plants located in the Sonoran Desert, Mexico. Four cDNA libraries were sequenced in an Illumina NextSeq 500 platform at the University of Arizona Genetics Core Facility. A total of 288,199,704 reads with 150 base pairs (bp) in length were sequenced in paired-end mode. After trimming, 243,194,888 (84.38%) cleaned short reads with at least 29 mean quality scores per read in the Phred scale and between 80 to 150 bp in length were obtained to carry out the assembly. After removing contaminating sequences, redundancy, and low-expressed transcripts, the assembly included 174,449 transcripts with an N50 value of 2,110 bp. Table 1 shows the different quality variables of the S. thurberi fruit peel transcriptome. BUSCO score showed that 85.4% are completed transcripts, although out of these, 37.2% were found to be duplicated. The resulting sequence data can be accessed at the SRA repository of the NCBI through the BioProject ID PRJNA1030439.

    Table 1.  Quality metrics of the Stenocereus thurberi fruit peel transcriptome.
    Metric Data
    Total transcripts 174,449
    N50 2,110
    Smallest transcript length (bp) 200
    Largest transcript length (bp) 19,114
    Mean transcript length (bp) 1,198.69
    GC (%) 41.33
    Total assembled bases 209,110,524
    TransRate score 0.05
    BUSCO score (%) C: 85.38 (S:48.22, D:37.16),
    F: 10.69, M: 3.93.
    Values were calculated through the TrinityStats function of Trinity and TransRate software. Completeness analysis was carried out through BUSCO by aligning the transcriptome to the Embryophyte database through BLAST with an E value threshold of 1 × 10−3. Complete (C), single (S), duplicated (D), fragmented (F), missing (M).
     | Show Table
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    A summary of the homology search in the main public protein database for the S. thurberi transcriptome is shown in Supplementary Table S1. From these databases, the higher homologous transcripts were found in RefSeq with 93,993 (53.87 %). Based on the E value distribution, for 41,685 (44%) and 68,853 (49%) of the hits, it was found a strong homology (E value lower than 1 × 10−50) to proteins in the Swiss-Prot and RefSeq databases, respectively (Supplementary Fig. S2a & b). On the other hand, 56,539 (52.34%) and 99,599 (71.11%) of the matches showed a percentage of identity higher than 60% in the Swiss-Prot and RefSeq databases, respectively (Supplementary Fig. S2c & d).

    Figure 1 shows the homology between transcripts from S. thurberi and proteins of commercial fruits, as well as proteins and transcripts of cacti. Transcripts from S. thurberi homologous to proteins from fruits of commercial interest avocado (P. americana), peach (P. persica), strawberry (F. vesca), orange (C. sinensis), and grapefruit (V. vinifera) ranged from 77,285 (44.30%) to 85,421 (48.96%), with 70,802 transcripts homologous to all the five fruit protein databases (Fig. 1a).

    Transcripts homologous to transcripts or proteins from the cactus dragon fruit (H. polyrhizus), prickly pear cactus (O. streptacantha), Mexican giant cardon (P. pringlei), and pitahaya (S. undatus) ranged from 76,238 (43.70%) to 114,933 (65.88%), with 64,009 transcripts homologous to all the four cactus databases (Fig. 1b). Further, out of the total of transcripts, 44,040 transcripts (25.25%) showed homology only to sequences from cactus, but not for model plants Arabidopsis, tomato, or the commercial fruits included in this study (Fig. 1c).

    Figure 1.  Venn diagram of the homology search results against model plants databases, commercial fruits, and cactus. The number in the diagram corresponds to the number of transcripts from S. thurberi homologous to sequences from that plant species. (a) Homologous to sequences from Fragaria vesca (Fa), Persea americana (Pa), Prunus persica (Pp), Vitis vinifera (Vv), and Citrus sinensis (Cs). (b) Homologous to sequences from Opuntia streptacantha (Of), Selenicereus undatus (Su), Hylocereus polyrhizus (Hp), and Pachycereus pringlei (Pap). (c) Homologous to sequences from Solanum lycopersicum (Sl), Arabidopsis thaliana (At), from the commercial fruits (Fa, Pa, Pp, Vv, and Cs), or the cactus included in this study (Of, Su, Hp, and Pap). Homologous searching was carried out by BLAST alignment (E value < 1 × 10−5). The Venn diagrams were drawn by ggVennDiagram in R Studio.

    A total of 45,970 (26.35%), 58,704 (33.65%), and 48,186 (27.65%) transcripts showed homology to transcription factors, transcriptional regulators, and protein kinases in the PlantTFDB, iTAK-TR, and iTAK-PK databases, respectively (Supplementary Tables S1, S9S11). For the PlantTFDB, the homologous transcripts belong to 57 transcriptional factors (TF) families (Fig. 2 & Supplementary Table S9), from which, the most frequent were the basic-helix-loop-helix (bHLH), myeloblastosis-related (MYB-related), NAM, ATAF, and CUC (NAC), ethylene responsive factor (ERF), and the WRKY domain families (WRKY) (Fig. 2).

    Figure 2.  Transcription factor (TF) families distribution of S. thurberi fruit peel transcriptome. The X-axis indicates the number of transcripts with hits to each TF family. Alignment to the PlantTFDB database by BLASTx was carried out with an E value threshold of 1 × 10−5. The bar graph was drawn by ggplot2 in R Studio.

    Based on the homology found and the functional domain searches, gene ontology terms (GO) were assigned to 68,559 transcripts (Supplementary Table S12). Figure 3 shows the top 20 GO terms assigned to the S. thurberi transcriptome, corresponding to the Biological Processes (BP) and Molecular Function (MF) categories. For BP, organic substance metabolic processes, primary metabolic processes, and cellular metabolic processes showed a higher number of transcripts (Supplementary Table S13). Further, for MF, organic cyclic compound binding, heterocyclic compound binding, and ion binding were the processes with the higher number of transcripts. S. thurberi transcripts were classified into 142 metabolic pathways from the KEGG database (Supplementary Table S14). The pathways with the higher number of transcripts recorded were pyruvate metabolism, glycerophospholipid metabolism, glycolysis/gluconeogenesis, and citrate cycle. Further, among the top 20 KEEG pathways, the cutin, suberin, and wax biosynthesis include more than 30 transcripts (Fig. 4).

    Figure 3.  Top 20 Gene Ontology (GO) terms assigned to the S. thurberi fruit peel transcriptome. Bars indicate the number of transcripts assigned to each GO term. Assignment of GO terms was carried out by Blast2GO with default parameters. BP and MF mean Biological Processes and Molecular Functions GO categories, respectively. The graph was drawn by ggplot2 in R Studio.
    Figure 4.  Top 20 KEGG metabolic pathways distribution in the S. thurberi fruit peel transcriptome. Bars indicate the number of transcripts assigned to each KEGG pathway. Assignment of KEGG pathways was carried out in the Blast2GO suite. The bar graph was drawn by ggplot2 in R Studio.

    Out of the total of transcripts, 43,391 (24.87%) were classified as lncRNA (Supplementary Tables S15 & S16). Figure 5 shows a comparison of the length (Fig. 5a) and expression (Fig. 5b) of lncRNA and coding RNA. Both length and expression values were higher in coding RNA than in lncRNA. In general, coding RNA ranged from 201 to 18,629 bp with a mean length of 1,507.18, whereas lncRNA ranged from 200 to 5,198 bp with a mean length of 481.51 (Fig. 5a). The higher expression values recorded from coding RNA and lncRNA were 12.83 and 9.45 log2(CPM), respectively (Fig. 5b).

    Figure 5.  Comparison of coding RNA and long non-coding RNA (lncRNA) from S. thurberi transcriptome. (a) Box plot of transcript length distribution. The Y-axis indicates the length of each transcript in base pairs. (b) Box plot of expression levels. The Y-axis indicates the log2 of the count per million of reads (log2(CPM)) recorded for each transcript. Expression levels were calculated by the edgeR package in R studio. (a), (b) The lines inside the boxes indicate the median. The higher and lower box limits represent the 75th and 25th percentiles, respectively. The box plots were drawn by ggplot2 in R Studio.

    To identify the transcripts without significant changes in expression between the four RNA-seq libraries, a differential expression analysis was carried out. Of the total of transcripts, 4,980 were not differentially expressed (NDE) at least in one paired comparison between the libraries (Supplementary Tables S17S20). Mean counts per million of reads (CPM) and coefficient of variation (CV)[44] were calculated for these NDE transcripts. Transcripts with a CV value lower than 0.113, corresponding with the percentile 5 of the CV, and a mean CPM higher than 1,138.06, corresponding with the percentile 95 of the mean CPM were used as filters to identify the most stably expressed transcripts (Supplementary Table S21). Based on its homology and its tentative biological function, five transcripts were selected to be tested as tentative reference genes. Besides, three NDE transcripts homologous to previously identified stable expressed reference genes in other species of cactus fruit[4143] were selected (Supplementary Table S22). Homology metrics for the eight tentative reference genes selected are shown in Supplementary Table S23. The primer sequences used to amplify the transcripts by qRT-PCR and their nucleotide sequence are shown in Supplementary Tables S24 & S25, respectively.

    The amplification specificity of the eight candidate reference genes determined by melting curves analysis is shown in Supplementary Fig. S3. For the eight tentative reference transcripts selected, the cycle threshold (Ct) values were recorded during sweet pitaya fruit development by qRT-PCR (Supplementary Table S26). The Ct values obtained ranged from 16.85 to 30.26 (Fig. 6a). Plastidic ATP/ADP-transporter (StTLC1) showed the highest Ct values with a mean of 27.34 (Supplementary Table S26). Polyubiquitin 3 (StUBQ3) showed the lowest Ct values in all five sweet pitaya fruit developmental stages (Fig. 6a).

    Figure 6.  Expression stability analysis of tentative reference genes. (a) Box plot of cycle threshold (Ct) distribution of candidate reference genes during sweet pitaya fruit development (10, 20, 30, 35, and 40 d after flowering). The black line inside the box indicates the median. The higher and lower box limits represent the 75th and 25th percentiles, respectively. (b) Bar chart of the geometric mean (geomean) of ranking values calculated by RefFinder for each tentative reference gene (X-axis). The lowest values indicate the best reference genes. (c) Bar chart of the pairwise variation analysis and determination of the optimal number of reference genes by the geNorm algorithm. A pairwise variation value lower than 0.15 indicates that the use of Vn/Vn + 1 reference genes is reliable for the accurate normalization of qRT-PCR data. The Ct data used in the analysis were calculated by qRT-PCR in a QIAquant 96 5 plex (QIAGEN) according to the manufacturer's protocol. The box plot and the bar graphs were drawn by ggplot2 and Excel programs, respectively. Abbreviations: Actin 7 (StACT7), alpha-tubulin (StTUA), elongation factor 1-alpha (StEF1a), COP1-interactive protein 1 (StCIP1), plasma membrane ATPase 4 (StPMA4), BEL1-like homeodomain protein 1 (StBLH1), polyubiquitin 3 (StUBQ3), and plastidic ATP/ADP-transporter (StTLC1).

    The best stability values calculated by NormFinder were 0.45, 0.51, 0.97, and 0.99, corresponding to the transcripts elongation factor 1-alpha (StEF1a), alpha-tubulin (StTUA), plastidic ATP/ADP-transporter (StTLC1), and actin 7 (StACT7), respectively (Supplementary Table S27). For BestKeeper, the most stable expressed transcripts were StUBQ3, StTUA, and StEF1a, with values of 0.72, 0.75, and 0.87, respectively. In the case of the delta Ct method[51], the transcripts StEF1a, StTUA, and StTLC1 showed the best stability.

    According to geNorm analysis, the most stable expressed transcripts were StTUA, StEF1a, StUBQ3, and StACT7, with values of 0.74, 0.74, 0.82, and 0.96, respectively. All the pairwise variation values (Vn/Vn + 1) were lower than 0.15, ranging from 0.019 for V2/V3 to 0.01 for V6/V7 (Fig. 6c). The V value of 0.019 obtained for V2/V3 indicates that the use of the best two reference genes StTUA and StEF1a is reliable enough for the accurate normalization of qRT-PCR data, therefore no third reference gene is required[47]. Except for BestKeeper analysis, StEF1a and StTUA were the most stable transcripts for all of the methods carried out in this study (Supplementary Table S27). The comprehensive ranking analysis indicates that StEF1a, followed by StTUA and StUBQ3, are the most stable expressed genes and are stable enough to be used as reference genes in qRT-PCR analysis during sweet pitaya fruit development (Fig. 6b).

    Three cuticle biosynthesis-related transcripts TRINITY_DN17030_c0_g1_i2, TRINITY_DN15394_c0_g1_i1, and TRINITY_DN23528_c1_g1_i1 tentatively coding for the enzymes cytochrome p450 family 77 subfamily A (CYP77A), Gly-Asp-Ser-Leu motif lipase/esterase 1 (GDSL1), and an ATP binding cassette transporter subfamily G member 11 (ABCG11/WBC11), respectively, were identified and quantified. The nucleotide sequence and predicted amino acid sequences of the three transcripts are shown in Supplementary File 1. The best homology match for StCYP77A (TRINITY_DN17030_c0_g1_i2) was for AtCYP77A4 (AT5G04660) from Arabidopsis and SmCYP77A2 (P37124) from eggplant (Solanum melongena) in the TAIR and Swiss-Prot databases, respectively (Supplementary Table S23).

    TransDecoder, InterPro, and TMHMM analysis showed that StCYP77A codes a polypeptide of 518 amino acids (aa) in length that comprises a cytochrome P450 E-class domain (IPR002401) and a transmembrane region (residues 10 to 32). The phylogenetic tree constructed showed that StCYP77A is grouped in a cluster with all the CYP77A2 proteins included in this analysis, being closer to CYP77A2 (XP_010694692) from B. vulgaris and Cgig2_012892 (KAJ8441854) from Carnegiea gigantean (Supplementary Fig. S4).

    StGDSL1 (TRINITY_DN15394_c0_g1_i1) alignment showed that it is homologous to a GDSL esterase/lipase from Arabidopsis (Q9LU14) and tomato (Solyc03g121180) (Supplementary Table S23). TransDecoder, InterPro, and SignalP analysis showed that StGDSL1 codes a polypeptide of 354 aa in length that comprises a GDSL lipase/esterase domain IPR001087 and a signal peptide with a cleavage site between position 25 and 26 (Supplementary Fig. S5).

    Supplementary Figure S6 shows the analysis carried out on the predicted amino acid sequence of StABCG11 (TRINITY_DN23528_c1_g1_i1). The phylogenetic tree constructed shows three clades corresponding to the ABCG13, ABCG12, and ABCG11 protein classes with bootstrap support ranging from 40% to 100% (Supplementary Fig. S6a). StABCG11 is grouped with all the ABCG11 transporters included in this study in a well-separated clade, being closely related to its tentative ortholog from C. gigantean Cgig2_004465 (KAJ8441854). InterPro and TMHMM results showed that the StABCG11 sequence contains an ABC-2 type transporter transmembrane domain (IPR013525; PF01061.27) with six transmembrane helices (Supplementary Fig. S6b).

    The predicted protein sequence of StABCG11 is 710 aa in length, holding the ATP binding domain (IPR003439; PF00005.30) and the P-loop containing nucleoside triphosphate hydrolase domain (IPR043926; PF19055.3) of the ABC transporters of the G family. Multiple sequence alignment shows that the Walker A and B motif sequence and the ABC signature[15] are conserved between the ABCG11 transporters from Arabidopsis, tomato, S. thurberi, and C. gigantean (Supplementary Fig. S6c).

    According to the results of the expression stability analysis (Fig. 6), four normalization strategies were tested to quantify the three cuticle biosynthesis-related transcripts during sweet pitaya fruit development. The four strategies consist of normalizing by StEF1a, StTUA, StUBQ3, or StEF1a+StTUA. Primer sequences used to quantify the transcripts StCYP77A (TRINITY_DN17030_c0_g1_i2), StGDSL1 (TRINITY_DN15394_c0_g1_i1), and StABCG11 (TRINITY_DN23528_c1_g1_i1) by qRT-PCR during sweet pitaya fruit development are shown in Supplementary Table S24.

    The three cuticle biosynthesis-related transcripts showed differences in expression during sweet pitaya fruit development (Supplementary Table S28). The same expression pattern was recorded for the three cuticle biosynthesis transcripts when normalization was carried out by StEF1a, StTUA, StUBQ3, or StEF1a + StTUA (Fig. 7). A higher expression of StCYP77A and StGDSL1 are shown at the 10 and 20 DAF, showing a decrease at 30, 35, and 40 DAF. StABCG11 showed a similar behavior, with a higher expression at 10 and 20 DAF and a reduction at 30 and 35 DAF. Nevertheless, unlike StCYP77A and StGDSL1, a significant increase at 40 DAF, reaching the same expression as compared with 10 DAF, is shown for StABCG11 (Fig. 7).

    Figure 7.  Expression analysis of cuticle biosynthesis-related transcripts StCYP77A, StGDSL1, and StABCG11 during sweet pitaya (Stenocereus thurberi) fruit development. Relative expression was calculated through the 2−ΔΔCᴛ method using elongation factor 1-alpha (StEF1a), alpha-tubulin (StTUA), polyubiquitin 3 (StUBQ3), or StEF1a + StTUA as normalizing genes at 10, 20, 30, 35, and 40 d after flowering (DAF). The Y-axis and error bars represent the mean of the relative expression ± standard error (n = 4−6) for each developmental stage in DAF. The Ct data for the analysis was recorded by qRT-PCR in a QIAquant 96 5 plex (QIAGEN) according to the manufacturer's protocol. The graph line was drawn by ggplot2 in R Studio. Abbreviations: cytochrome p450 family 77 subfamily A (StCYP77A), Gly-Asp-Ser-Leu motif lipase/esterase 1 (StGDSL1), and ATP binding cassette transporter subfamily G member 11 (StABCG11).

    Characteristics of a well-assembled transcriptome include an N50 value closer to 2,000 bp, a high percentage of conserved transcripts completely assembled (> 80%), and a high proportion of reads mapping back to the assembled transcripts[52]. In the present study, the first collection of 174,449 transcripts from S. thurberi fruit peel are reported. The generated transcriptome showed an N50 value of 2,110 bp, a TransRate score of 0.05, and a GC percentage of 41.33 (Table 1), similar to that reported for other de novo plant transcriptome assemblies[53]. According to BUSCO, 85.4% of the orthologous genes from the Embryophyta databases completely matched the S. thurberi transcriptome, and only 3.9% were missing (Table 1). These results show that the S. thurberi transcriptome generated is not fragmented, and it is helpful in predicting the sequence of almost all the transcripts expressed in sweet pitaya fruit peel[24].

    The percentage of transcripts homologous found, E values, and identity distribution (Supplementary Tables S1 & S2; Supplementary Fig. S2) were similar to that reported in the de novo transcriptome assembly for non-model plants and other cactus fruits[4143,54] and further suggests that the transcriptome assembled of S. thurberi peel is robust[52]. Of the total of transcripts, 70,802 were common to all the five commercial fruit protein databases included in this study, which is helpful for the search for conserved orthologous involved in fruit development and ripening (Fig. 2a). A total of 34,513 transcripts (20%) show homology only to sequences in the cactus's databases, but not in the others (Supplementary Tables S1 & S2; Fig. 1c). This could suggest that a significant conservation of sequences among plants of the Cactaceae family exists which most likely are to have a function in this species adaptation to desert ecosystems.

    To infer the biological functionality represented by the S. thurberi fruit peel transcriptome, gene ontology (GO) terms and KEGG pathways were assigned. Of the main metabolic pathways assigned, 'glycerolipid metabolism' and 'cutin, suberine, and wax biosynthesis' suggests an active cuticle biosynthesis in pitaya fruit peel (Fig. 4). In agreement with the above, the main GO terms assigned for the molecular function (MF) category were 'organic cyclic compound binding', 'transmembrane transporter activity', and 'lipid binding' (Fig. 3). For the biological processes (BP) category, the critical GO terms for the present research are 'cellular response to stimulus', 'response to stress', 'anatomical structure development', and 'transmembrane transport', which could suggest the active development of the fruit epidermis and cuticle biosynthesis for protection to stress.

    The most frequent transcription factors (TF) families found in S. thurberi transcriptome were NAC, WRKY, bHLH, ERF, and MYB-related (Fig. 2), which had been reported to play a function in the tolerance to abiotic stress in plants[55,56]. Although the role of NAC, WRKY, bHLH, ERF, and MYB TF in improving drought tolerance in relevant crop plants has been widely documented[57,58], their contribution to the adaptation of cactus to arid ecosystems has not yet been elucidated and further experimental pieces of evidence are needed.

    It has been reported that the heterologous expression of ERF TF from Medicago truncatula induces drought tolerance and cuticle wax biosynthesis in Arabidopsis leaf[59]. In tomato fruits, the gene SlMIXTA-like which encodes a MYB transcription factor avoids water loss through the positive regulation of genes related to the biosynthesis and transport of cuticle compounds[22]. Despite the relevant role of cuticles in maintaining cactus physiology in desert environments, experimental evidence showing the role of the different TF-inducing cuticle biosynthesis has yet to be reported for cactus fruits.

    Out of the transcripts, 43,391 were classified as lncRNA (Supplementary Tables S15 & S16). This is the first report of lncRNA identification for the species S. thurberi. In fruits, 3,679 lncRNA has been identified from tomato[26], 3,330 from peach (P. persica)[29], 3,857 from melon (Cucumis melo)[28], 2,505 from hot pepper (Capsicum annuum)[27], and 3,194 from pomegranate (Punica granatum)[36]. Despite the stringent criteria to classify the lncRNA of sweet pitaya fruit (S. thurberi), a higher number of lncRNAs are shown when compared with previous reports. This finding is most likely due to the higher level of redundancy found during the transcriptome analysis. To reduce this redundancy, further efforts to achieve the complete genome assembly of S. thurberi are needed.

    Previous studies showed that lncRNA is shorter and has lower expression levels than coding RNA[6062]. In agreement with those findings, both the length and expression values of lncRNA from S. thurberi were lower than coding RNA (Fig. 5). It has been suggested that lncRNA could be involved in the biosynthesis of cuticle components in cabbage[61] and pomegranate[36] and that they could be involved in the tolerance to water deficit through the regulation of cuticle biosynthesis in wild banana[60]. Nevertheless, the molecular mechanism by which lncRNA may regulate the cuticle biosynthesis in S. thurberi fruits has not yet been elucidated.

    A relatively constant level of expression characterizes housekeeping genes because they are involved in essential cellular functions. These genes are not induced under specific conditions such as biotic or abiotic stress. Because of this, they are very useful as internal reference genes for qRT-PCR data normalization[63]. Nevertheless, their expression could change depending on plant species, developmental stages, and experimental conditions[64]. Reliable reference genes for a specific experiment in a given species must be identified to carry out an accurate qRT-PCR data normalization[63]. An initial screening of the transcript expression pattern through RNA-seq improves the identification of stably expressed transcripts by qRT-PCR[44,64].

    Identification of stable expressed reference transcripts during fruit development has been carried out in blueberry (Vaccinium bracteatum)[65], kiwifruit (Actinidia chinensis)[66], peach (P. persica)[67], apple (Malus domestica)[68], and soursop (Annona muricata)[69]. These studies include the expression stability analysis through geNorm, NormFinder, and BestKeeper algorithms[68,69], some of which are supported in RNA-seq data[65,66]. Improvement of expression stability analysis by RNA-seq had led to the identification of non-previously reported reference genes with a more stable expression during fruit development than commonly known housekeeping genes in grapevine (V. vinifera)[44], pear (Pyrus pyrifolia and P. calleryana)[64], and pepper (C. annuum)[70].

    For fruits of the Cactaceae family, only a few studies identifying reliable reference genes have been reported[4143]. Mainly because gene expression analysis has not been carried out previously for sweet pitaya (S. thurberi), the RNA-seq data generated in this work along with geNorm, NormFinder, BestKeeper, and RefFinder algorithms were used to identify reliable reference genes. The comprehensive ranking analysis showed that out of the eight candidate genes tested, StEF1a followed by StTUA and StUBQ3 were the most stable (Fig. 6b). All the pairwise variation values (Vn/Vn + 1) were lower than 0.15 (Fig. 6c), which indicates that StEF1a, StTUA, and StUBQ3 alone or the use of StEF1a and StTUA together are reliable enough to normalize the gene expression data generated by qRT-PCR.

    The genes StEF1a, StTUA, and StUBQ3 are homologous to transcripts found in the cactus species known as dragonfruit (Hylocereus monacanthus and H. undatus)[41], which have been tested as tentative reference genes during fruit development. EF1a has been proposed as a reliable reference gene in the analysis of changes in gene expression of dragon fruit (H. monacanthus and H. undatus)[41], peach (P. persica)[67], apple (M. domestica)[68], and soursop (A. muricata)[69]. According to the expression stability analysis carried out in the present study (Fig. 6) four normalization strategies were designed. The same gene expression pattern was recorded for the three target transcripts evaluated when normalization was carried out by the genes StEF1a, StTUA, StUBQ3, or StEF1a + StTUA (Fig. 7). Further, these data indicates that these reference genes are reliable enough to be used in qRT-PCR experiments during fruit development of S. thurberi.

    The plant cuticle is formed by two main layers: the cutin, composed mainly of mid-chain oxygenated LC fatty acids, and the cuticular wax, composed mainly of very long-chain (VLC) fatty acids, and their derivates VLC alkanes, VLC primary alcohols, VLC ketones, VLC aldehydes, and VLC esters[3]. In Arabidopsis CYP77A4 and CYP77A6 catalyze the synthesis of midchain epoxy and hydroxy ω-OH long-chain fatty acids, respectively[10,11], which are the main components of fleshy fruit cuticle[3].

    The functional domain search carried out in the present study showed that StCYP77A comprises a cytochrome P450 E-class domain (IPR002401) and a membrane-spanning region from residues 10 to 32 (Supplementary Fig. S4). This membrane-spanning region has been previously characterized in CYP77A enzymes from A. thaliana and Brassica napus[11,71]. It suggests that the protein coded by StCYP77A could catalyze the oxidation of fatty acids embedded in the endoplasmic reticulum membrane of the epidermal cells of S. thurberi fruit. Phylogenetic analysis showed that StCYP77A was closer to proteins from its phylogenetic-related species B. vulgaris (BvCYP772; XP_010694692) and C. gigantea (Cgig2_012892) (Supplementary Fig. S4). StCYP77A, BvCYP77A2, and Cgig2_012892 were closer to SlCYP77A2 and SmCYP77A2 than to CYP77A4 and CYP77A6 proteins, suggesting that StCYP77A (TRINITY_DN17030_c0_g1_i2) could correspond to a CYP77A2 protein.

    Five CYP77A are present in the Arabidopsis genome, named CYP77A4, CYP77A5, CYP77A6, CYP77A7, and CYP77A9, but their role in cuticle biosynthesis has only been reported for CYP77A4 and CYP77A6[72]. It has been suggested that CYP77A2 from eggplant (S. torvum) could contribute to the defense against fungal phytopathogen infection by the synthesis of specific compounds[13]. In pepper fruit (C. annuum), the expression pattern of CYP77A2 (A0A1U8GYB0) and ABCG11 (LOC107862760) suggests a role of CYP77A2 and ABCG11 in cutin biosynthesis at the early stages of pepper fruit development[14].

    In the case of the protein encoded by StGDSL1 (354 aa), the length found in this work is similar to the length of its homologous from Arabidopsis (AT3G16370) and tomato (Solyc03g121180) (Supplementary Fig. S5). A GDSL1 protein named CD1 polymerizes midchain oxygenated ω-OH long-chain fatty acids to form the cutin polyester in the extracellular space of tomato fruit peel[20,21]. It has been suggested that the 25-amino acid N-signal peptide found in StGDSL1 (Supplementary Fig. S5), previously reported in GDSL1 from Arabidopsis, B. napus, and tomato, plays a role during the protein exportation to the extracellular space[21,73].

    A higher expression of StCYP77A, StGDSL1, and StABCG11 is shown at the 10 and 20 DAF of sweet pitaya fruit development (Fig. 7), suggesting the active cuticle biosynthesis at the early stages of sweet pitaya fruit development. In agreement with that, two genes coding for GDSL lipase/hydrolases from tomato named SGN-U583101 and SGN-U579520 are highly expressed in the early stages and during the expansion stages of tomato fruit development, but their expression decreases in later stages[74]. It has been shown that the expression of GDSL genes, like CD1 from tomato, is higher in growing fruit[20,21]. Like tomato, the increase in expression of StCYP77A and StGDSL1 shown in pitaya fruit development could be due to an increase in cuticle deposition during the expansion of the fruit epidermis[20].

    The phylogenetic analysis, the functional domains, and the six transmembrane helices found in the StABCG11 predicted protein (Supplementary Fig. S6), suggests that it is an ABCG plasma membrane transporter of sweet pitaya[15]. Indeed, an increased expression of StABCG11 at 40 DAF was recorded in the present study (Fig. 7). Further, this data strongly suggests that it could be playing a relevant role in the transport of cuticle components at the beginning and during sweet pitaya fruit ripening.

    In Arabidopsis, ABCG11 (WBC11) exports cuticular wax and cutin compounds from the plasma membrane[15,75]. It has been reported that a high expression of the ABC plasma membrane transporter from mango MiWBC11 correlates with a higher cuticle deposition during fruit development[7]. The expression pattern for StABCG11, StCYP77A, and StGDSL1 suggests a role of StABCG11 as a cutin compound transporter in the earlier stages of sweet pitaya fruit development (Fig. 7). Further, its increase at 40 DAF suggests that it could be transporting cuticle compounds other than oxygenated long-chain fatty acids, or long-chain fatty acids that are not synthesized by StCYP77A and StGDSL1 in the later stages of fruit development.

    Like sweet pitaya, during sweet cherry fruit (Prunus avium) development, the expression of PaWCB11, homologous to AtABCG11 (AT1G17840), increases at the earlier stages of fruit development decreases at the intermediate stages, and increases again at the later stages[76]. PaWCB11 expression correlated with cuticle membrane deposition at the earlier and intermediate stages of sweet cherry fruit development but not at the later[76]. The increased expression of StABCG11 found in the present study could be due to the increased transport of cuticular wax compounds, such as VLC fatty acids and their derivates, in the later stages of sweet pitaya development[15,75].

    Cuticular waxes make up the smallest amount of the fruit cuticle. Even so, they mainly contribute to the impermeability of the fruit's epidermis[3]. An increase in the transport of cuticular waxes at the beginning of the ripening stage carried out by ABCG transporters could be due to a greater need to avoid water loss and to maintain an adequate amount of water during the ripening of the sweet pitaya fruit. Nevertheless, further expression analysis of cuticular wax biosynthesis-related genes, complemented with chemical composition analysis of cuticles could contribute to elucidating the molecular mechanism of cuticle biosynthesis in cacti and their physiological contribution during fruit development.

    In this study, the transcriptome of the sweet pitaya (S. thurberi) fruit peel was assembled for the first time. The reference genes found here are a helpful tool for further gene expression analysis in sweet pitaya fruit. Transcripts tentatively involved in cuticle compound biosynthesis and transport are reported for the first time in sweet pitaya. The results suggest a relevant role of cuticle compound biosynthesis and transport at the early and later stages of fruit development. The information generated will help to improve the elucidation of the molecular mechanism of cuticle biosynthesis in S. thurberi and other cactus species in the future. Understanding the cuticle's physiological function in the adaptation of the Cactaceae family to harsh environmental conditions could help design strategies to increase the resistance of other species to face the increase in water scarcity for agricultural production predicted for the following years.

    The authors confirm contribution to the paper as follows: study conception and design: Tiznado-Hernández ME, Tafolla-Arellano JC, García-Coronado H, Hernández-Oñate MÁ; data collection: Tiznado-Hernández ME, Tafolla-Arellano JC, García-Coronado H, Hernández-Oñate MÁ; analysis and interpretation of results: Tiznado-Hernández ME, García-Coronado H, Hernández-Oñate MÁ, Burgara-Estrella AJ; draft manuscript preparation: Tiznado-Hernández ME, García-Coronado H. All authors reviewed the results and approved the final version of the manuscript.

    All data generated or analyzed during this study are included in this published article and its supplementary information files. The sequence data can be accessed at the Sequence Read Archive (SRA) repository of the NCBI through the BioProject ID PRJNA1030439.

    The authors wish to acknowledge the financial support of Consejo Nacional de Humanidades, Ciencias y Tecnologías de México (CONAHCYT) through project number 579: Elucidación del Mecanismo Molecular de Biosíntesis de Cutícula Utilizando como Modelo Frutas Tropicales. We appreciate the University of Arizona Genetics Core and Illumina for providing reagents and equipment for library sequencing. The author, Heriberto García-Coronado (CVU 490952), thanks the CONAHCYT (acronym in Spanish) for the Ph.D. scholarship assigned (749341). The author, Heriberto García-Coronado, thanks Dr. Edmundo Domínguez-Rosas for the technical support in bioinformatics for identifying long non-coding RNA.

  • The authors declare that they have no conflict of interest.

  • [1]

    Zhou L, Shen W. 2019. The causes and prevention and control of trampling accidents in large group activities. Journal of Henan Police Academy 28:24−29

    doi: 10.16231/j.cnki.jhpc.2019.03.003

    CrossRef   Google Scholar

    [2]

    Chen R, Wang L, Xu L, Wu H. 2021. Research and practice on the creation method of demonstration cities of safety development from the perspective of government. China Safety Production Science and Technology 17:189−93

    Google Scholar

    [3]

    Zhang ZX, Sun Y. 2019. Exploring the collaborative governance mechanism of multiple subjects in public crises: the example of the "11-18" fire in Beijing. Administrative Reform 2019:77−83

    doi: 10.14150/j.cnki.1674-7453.2019.04.010

    CrossRef   Google Scholar

    [4]

    Zhang Y. 2019. Research on risk diagnosis and adaptive mechanism of urban areas oriented to fire control and safety. Thesis. Capital University of Economics and Business, China.

    [5]

    Niu X. 2019. Research on fault prediction algorithm based on DiPCA. Thesis. North University of Technology, China.

    [6]

    Fu Q. 2021. Structural safety in the design of building decoration and renovation. Shanghai Construction Science and Technology 2021(1):41−44

    Google Scholar

    [7]

    Ye D. 2021. Research on the mechanism of active information release by leading cadres in sudden and sensitive events. China Emergency Management Science 2021(7):85−96

    Google Scholar

    [8]

    Fan Q, Guo W, Feng Y. 2009. 30 years of development of bibliometric research in China. Intelligence work 2009(3):30−33+60

    Google Scholar

    [9]

    Li J, Reniers G, Cozzani V, Khan F. 2017. A bibliometric analysis of peer-reviewed publications on domino effects in the process industry. Journal of Loss Prevention in the Process Industries 49:103−10

    doi: 10.1016/j.jlp.2016.06.003

    CrossRef   Google Scholar

    [10]

    Li W, Zhao Y. 2015. Bibliometric analysis of global environmental assessment research in a 20-year period. Environmental Impact Assessment Review 50:158−66

    doi: 10.1016/j.eiar.2014.09.012

    CrossRef   Google Scholar

    [11]

    Sun Y, Grimes S. 2016. The emerging dynamic structure of national innovation studies: A bibliometric analysis. Scientometrics 106:17−40

    doi: 10.1007/s11192-015-1778-0

    CrossRef   Google Scholar

    [12]

    Xu W, Zou Z, Pei J, Huang L. 2018. Longitudinal trend of global artemisinin research in chemistry subject areas (1983–2017). Bioorganic & Medicinal Chemistry 26:5379−87

    doi: 10.1016/j.bmc.2018.09.030

    CrossRef   Google Scholar

    [13]

    Fang C, Zhang J, Qiu W. 2017. Online classified advertising: a review and bibliometric analysis. Scientometrics 113:1481−511

    doi: 10.1007/s11192-017-2524-6

    CrossRef   Google Scholar

    [14]

    Tsai HH. 2015. The research trends forecasted by bibliometric methodology: a case study in e-commerce from 1996 to July 2015. Scientometrics 105:1079−89

    doi: 10.1007/s11192-015-1719-y

    CrossRef   Google Scholar

    [15]

    Xing Y, Guo Z, Su W, Wen W, Wang X, et al. 2021. A review of the hot spot analysis and the research status of single-atom catalysis based on the bibliometric analysis. New Journal of Chemistry 45:4253−69

    doi: 10.1039/D0NJ05673A

    CrossRef   Google Scholar

    [16]

    Xu X, Chen X, Jia F, Brown S, Gong Y, et al. 2018. Supply chain finance: A systematic literature review and bibliometric analysis. International Journal of Production Economics 204:160−73

    doi: 10.1016/j.ijpe.2018.08.003

    CrossRef   Google Scholar

    [17]

    Wu Y, Wan Y, Zhang F. 2018. Characteristics and Trends of C-H Activation Research: A Review of Literature. Current Organic Synthesis 15:781−92

    doi: 10.2174/1570179415666180426115417

    CrossRef   Google Scholar

    [18]

    Su M, Peng H, Li S. 2021. A visualized bibliometric analysis of mapping research trends of machine learning in engineering (MLE). Expert Systems with Applications 186:115728

    doi: 10.1016/j.eswa.2021.115728

    CrossRef   Google Scholar

    [19]

    Guo Y, Huang Z, Guo J, Li H, Guo X, et al. 2019. Bibliometric analysis on smart cities research. Sustainability 11:3606

    doi: 10.3390/su11133606

    CrossRef   Google Scholar

    [20]

    Zhang Y, Lu J, Liu F, Liu Q, Porter A, et al. 2018. Does deep learning help topic extraction? A kernel k-means clustering method with word embedding Journal of Informetrics 12:1099−117

    doi: 10.1016/j.joi.2018.09.004

    CrossRef   Google Scholar

    [21]

    Wu H, Sun Z, Tong L, Wang Y, Yan H, et al. 2021. Bibliometric analysis of global research trends on male osteoporosis: a neglected field deserves more attention. Archives of Osteoporosis 16:154

    doi: 10.1007/s11657-021-01016-2

    CrossRef   Google Scholar

    [22]

    Liao KY, Wang YH, Li HC, Chen TJ, Hwang SJ. 2021. COVID-19 publications in family medicine journals in 2020: A PubMed-based bibliometric analysis. International Journal of Environmental Research and Public Health 18:7748

    doi: 10.3390/ijerph18157748

    CrossRef   Google Scholar

    [23]

    Li S, Wang H, Zheng H, Li N, Sun C, et al. 2020. Bibliometric analysis of pediatric liver transplantation research in PubMed from 2014 to 2018. Medical Science Monitor 26:e922517

    doi: 10.12659/MSM.922517

    CrossRef   Google Scholar

    [24]

    He G, Yang Y, Chen Z, Gu C, Pan Z. 2013. A review of behavior mechanisms and crowd evacuation animation in emergency exercises. Journal of Zhejiang University: Science C 14:477−85

    doi: 10.1631/jzus.CIDE1301

    CrossRef   Google Scholar

    [25]

    Li Y, Chen M, Dou Z, Zheng X, Cheng Y, et al. 2019. A review of cellular automata models for crowd evacuation. Physica A: Statistical Mechanics and its Applications 526:120752

    doi: 10.1016/j.physa.2019.03.117

    CrossRef   Google Scholar

    [26]

    Zhou M, Dong H, Ioannou PA, Zhao Y, Wang F. 2019. Guided crowd evacuation: approaches and challenges. IEEE - CAA Journal of Automatica Sinica 6:1081−94

    doi: 10.1109/JAS.2019.1911672

    CrossRef   Google Scholar

    [27]

    Ding N, Chen T, Zhu Y, Lu Y. 2021. State-of-the-art high-rise building emergency evacuation behavior. Physica A:Statistical Mechanics and its Applications 561:125168

    doi: 10.1016/j.physa.2020.125168

    CrossRef   Google Scholar

    [28]

    Zhu K, Wang B, Wang J, Guo N, Mei P. 2021. Assessing Individual Evacuation Performance Moving on Long Stairs in a Subway Station: A Field Experiment. Fire Technology 57:2159−79

    doi: 10.1007/s10694-021-01114-0

    CrossRef   Google Scholar

    [29]

    Jia G, Ma R, Hu Z. 2019. Review of urban transportation network design problems based on CiteSpace. Mathematical Problems in Engineering 2019:5735702

    doi: 10.1155/2019/5735702

    CrossRef   Google Scholar

    [30]

    van Nunen K, Li J, Reniers G, Ponnet K. 2018. Bibliometric analysis of safety culture research. Safety Science 108:248−58

    doi: 10.1016/j.ssci.2017.08.011

    CrossRef   Google Scholar

    [31]

    Luo L, Fu Z, Cheng H, Yang LZ. 2018. Update schemes of multi-velocity floor field cellular automaton for pedestrian dynamics. Physica A:Statistical Mechanics and Its Applications 491:946−63

    doi: 10.1016/j.physa.2017.09.049

    CrossRef   Google Scholar

    [32]

    Chen S, Zhang Y, Dai W, Qi S, Tian W, et al. 2020. Publication trends and hot spots in postoperative cognitive dysfunction research: A 20-year bibliometric analysis. Journal of Clinical Anesthesia 67:110012

    doi: 10.1016/j.jclinane.2020.110012

    CrossRef   Google Scholar

    [33]

    Fu J, Ding J. 2019. Comparison of visualization principles between CiteSpace and VOSviewer software. Journal of Library and Information Science in Agriculture 31(10):31−37

    doi: 10.13998/j.cnki.issn1002-1248.2019.10.19-0776

    CrossRef   Google Scholar

    [34]

    van Eck NJ, Waltman L. 2010. Software survey: VOSviewer, a computer program for bibliometric mapping. Scientometrics 84:523−38

    doi: 10.1007/s11192-009-0146-3

    CrossRef   Google Scholar

    [35]

    Fan R, Feng Y, Chen L, Zhao K, Zhang S, et al. 2021. Robot-assisted single-port laparoscopic surgery in urology. Journal of Robotic Surgery (in English and Chinese) 202:476−84

    Google Scholar

    [36]

    Song W, Xu X, Wang B, Ni S. 2006. Simulation of evacuation processes using a multi-grid model for pedestrian dynamics. Physica A:Statistical Mechanics and Its Applications 363:492−500

    doi: 10.1016/j.physa.2005.08.036

    CrossRef   Google Scholar

    [37]

    Lo SM, Huang HC, Wang P, Yuen KK. 2006. A game theory based exit selection model for evacuation. Fire Safety Journal 41:364−69

    doi: 10.1016/j.firesaf.2006.02.003

    CrossRef   Google Scholar

    [38]

    Song W, Yu Y, Wang B, Fan W. 2006. Evacuation behaviors at exit in CA model with force essentials: A comparison with social force model. Physica A: Statistical Mechanics and Its Applications 371:658−666

    doi: 10.1016/j.physa.2006.03.027

    CrossRef   Google Scholar

    [39]

    Yang L, Zhao D, Li J, Fang T. 2005. Simulation of the kin behavior in building occupant evacuation based on Cellular Automaton. Building and Environment 40:411−15

    doi: 10.1016/j.buildenv.2004.08.005

    CrossRef   Google Scholar

    [40]

    Lo SM, Fang Z, Lin P, Zhi GS. 2004. An evacuation model: the SGEM package. Fire Safety Journal 39:169−90

    doi: 10.1016/j.firesaf.2003.10.003

    CrossRef   Google Scholar

    [41]

    Zheng X, Zhong T, Liu M. 2009. Modeling crowd evacuation of a building based on seven methodological approaches. Building and Environment 44:437−45

    doi: 10.1016/j.buildenv.2008.04.002

    CrossRef   Google Scholar

    [42]

    Huang H, Guo R. 2008. Static floor field and exit choice for pedestrian evacuation in rooms with internal obstacles and multiple exits. Physical Review E 78:21131

    doi: 10.1103/physreve.78.021131

    CrossRef   Google Scholar

    [43]

    Guo R, Huang H, Wong S. 2012. Route choice in pedestrian evacuation under conditions of good and zero visibility: Experimental and simulation results. Transportation Research Part B: Methodological 46:669−86

    doi: 10.1016/j.trb.2012.01.002

    CrossRef   Google Scholar

    [44]

    Shi J, Ren A, Chen C. 2009. Agent-based evacuation model of large public buildings under fire conditions. Automation in Construction 18:338−47

    doi: 10.1016/j.autcon.2008.09.009

    CrossRef   Google Scholar

    [45]

    Hou L, Liu J, Pan X, Wang B. 2014. A social force evacuation model with the leadership effect. Physica A: Statistical Mechanics and its Applications 400:93−99

    doi: 10.1016/j.physa.2013.12.049

    CrossRef   Google Scholar

    [46]

    Liu H, Xu B, Lu D, Zhang G. 2018. A path planning approach for crowd evacuation in buildings based on improved artificial bee colony algorithm. Applied Soft Computing 68:360−76

    doi: 10.1016/j.asoc.2018.04.015

    CrossRef   Google Scholar

    [47]

    Liu H, Liu B, Zhang H, Li L, Qin X, et al. 2018. Crowd evacuation simulation approach based on navigation knowledge and two-layer control mechanism. Information Sciences 436:247−67

    doi: 10.1016/j.ins.2018.01.023

    CrossRef   Google Scholar

    [48]

    Lu L, Chan C, Wang J, Wang W. 2017. A study of pedestrian group behaviors in crowd evacuation based on an extended floor field cellular automaton model. Transportation Research Part C: Emerging Technologies 81:317−329

    doi: 10.1016/j.trc.2016.08.018

    CrossRef   Google Scholar

    [49]

    Zhao Y, Li M, Lu X, Tian L, Yu Z, et al. 2017. Optimal layout design of obstacles for panic evacuation using differential evolution. Physica A: Statistical Mechanics and Its Applications 465:175−94

    doi: 10.1016/j.physa.2016.08.021

    CrossRef   Google Scholar

    [50]

    Chen J, Lo SM, Ma J. 2017. Pedestrian ascent and descent fundamental diagram on stairway. Journal of Statistical Mechanics: Theory and Experiment, 2017(8):83403

    doi: 10.1088/1742-5468/aa79ad

    CrossRef   Google Scholar

    [51]

    Liu B, Liu H, Zhang H, Qin X. 2018. A social force evacuation model driven by video data. Simulation Modelling Practice and Theory 84:190−203

    doi: 10.1016/j.simpat.2018.02.007

    CrossRef   Google Scholar

    [52]

    Shi Z, Zhang J, Song W. 2021. Where luggage-related facilities should be placed along passageways in traffic hubs: Right, left, or in the middle? Physica A: Statistical Mechanics and its Applications 583:126290

    doi: 10.1016/j.physa.2021.126290

    CrossRef   Google Scholar

    [53]

    Chen L, Tang T, Huang H, Wu J, Song Z. 2018. Modeling pedestrian flow accounting for collision avoidance during evacuation. Simulation Modelling Practice and Theory 82:1−11

    doi: 10.1016/j.simpat.2017.12.011

    CrossRef   Google Scholar

    [54]

    Yang X, Dong H, Wang Q, Chen Y, Hu X. 2014. Guided crowd dynamics via modified social force model. Physica A: Statistical Mechanics and Its Applications 411:63−73

    doi: 10.1016/j.physa.2014.05.068

    CrossRef   Google Scholar

    [55]

    Qu Y, Gao Z, Xiao Y, Li X. 2014. Modeling the pedestrian's movement and simulating evacuation dynamics on stairs. Safety Science 70:189−201

    doi: 10.1016/j.ssci.2014.05.016

    CrossRef   Google Scholar

    [56]

    Tan L, Hu M, Lin H. 2015. Agent-based simulation of building evacuation: Combining human behavior with predictable spatial accessibility in a fire emergency. Information Sciences 295:53−66

    doi: 10.1016/j.ins.2014.09.029

    CrossRef   Google Scholar

    [57]

    Liu X, Song W, Zhang J. 2009. Extraction and quantitative analysis of microscopic evacuation characteristics based on digital image processing. Physica A: Statistical Mechanics and Its Applications 388:2717−2726

    doi: 10.1016/j.physa.2009.03.017

    CrossRef   Google Scholar

    [58]

    Li D, Han B. 2015. Behavioral effect on pedestrian evacuation simulation using cellular automata. Safety Science 80:41−55

    doi: 10.1016/j.ssci.2015.07.003

    CrossRef   Google Scholar

    [59]

    Guo R, Huang HJ, Wong SC. 2011. Collection, spillback, and dissipation in pedestrian evacuation: A network-based method. Transportation Research Part B: Methodological 45:490−506

    doi: 10.1016/j.trb.2010.09.009

    CrossRef   Google Scholar

    [60]

    Zheng Y, Jia B, Li X, Zhu N. 2011. Evacuation dynamics with fire spreading based on cellular automaton. Physica A: Statistical Mechanics and its Applications 390:3147−56

    doi: 10.1016/j.physa.2011.04.011

    CrossRef   Google Scholar

    [61]

    Li J (Ed). 2018. Principles and Applications of Scientific Knowledge Graph - Beginner's Guide to VOSviewer and CitNet Explorer. Beijing: Higher Education Press.

    [62]

    Helbing D, Farkas I, Vicsek T. 2000. Simulating dynamical features of escape panic. Nature 407:487−90

    doi: 10.1038/35035023

    CrossRef   Google Scholar

    [63]

    Burstedde C, Klauck K, Schadschneider A, Zittartz J. 2001. Simulation of pedestrian dynamics using a two-dimensional cellular automaton. Physica A: Statistical Mechanics and its Applications 295:507−25

    doi: 10.1016/S0378-4371(01)00141-8

    CrossRef   Google Scholar

    [64]

    Callon M, Courtial JP, Turner WA, Bauin S. 1983. From translations to problematic networks: An introduction to co-word analysis. Social Science Information Sur Les Sciences Sociales 22:191−235

    doi: 10.1177/053901883022002003

    CrossRef   Google Scholar

    [65]

    Jin RY, Zou PXW, Piroozfar P, Wood H, Yang Y, et al. 2019. A science mapping approach based review of construction safety research. Safety Science 113:285−97

    doi: 10.1016/j.ssci.2018.12.006

    CrossRef   Google Scholar

    [66]

    Dang P, Zhu J, Pirasteh S, Li W, You J, et al. 2021. A chain navigation grid based on cellular automata for large-scale crowd evacuation in virtual reality. International Journal of Applied Earth Observation and Geoinformation 103:105207

    doi: 10.1016/j.jag.2021.102507

    CrossRef   Google Scholar

    [67]

    Wang H, Xu T, Li F. 2021. A novel emergency evacuation model of subway station passengers considering personality traits. Sustainability 13:10463

    doi: 10.3390/su131810463

    CrossRef   Google Scholar

    [68]

    Wang P, Cao S. 2019. Simulation of pedestrian evacuation strategies under limited visibility. Physics Letters A 383:825−32

    doi: 10.1016/j.physleta.2018.12.017

    CrossRef   Google Scholar

    [69]

    Huang R, Zhao X, Yuan Y, Yu Q, Zhou C, et al. 2021. Experimental study on evacuation behaviour of passengers in a high-deck coach: A Chinese case study. Physica A: Statistical Mechanics and Its Applications 579:126120

    doi: 10.1016/j.physa.2021.126120

    CrossRef   Google Scholar

    [70]

    Wang JH, Lo SM, Sun JH, Wang QS, Mu HL. 2012. Qualitative simulation of the panic spread in large-scale evacuation. SIMULATION 88:1465−74

    doi: 10.1177%2F0037549712456884

    CrossRef   Google Scholar

    [71]

    Wang JH, Lo SM, Wang QS, Sun JH, Mu HL. 2013. Risk of large-scale evacuation based on the effectiveness of rescue strategies under different crowd densities. Risk Analysis 33:1553−63

    doi: 10.1111/j.1539-6924.2012.01923.x

    CrossRef   Google Scholar

    [72]

    Cui L, Ding G, Wang L, Li L. 2016. Behavior rehearsal and simulation of audiences in large-scale activity. Computer Simulation 33:265−68

    Google Scholar

    [73]

    Zhan S, Chen L, Chen P, Ye Y. 2019. A vehicle route planning method of two-phase large-scale crowd evacuation in typhoon relief activities. Mathematical Problems in Engineering 2019:9539746

    doi: 10.1155/2019/9539746

    CrossRef   Google Scholar

    [74]

    Ma K, Zhang P, Mao Z. 2020. Study on large-scale crowd evacuation method in cultural museum using mutation prediction RFID. Personal and Ubiquitous Computing 24:177−91

    doi: 10.1007/s00779-019-01256-7

    CrossRef   Google Scholar

    [75]

    Mei P, Ding G, Jin Q, Zhang F. 2021. Research on emotion simulation method of large-scale crowd evacuation under particle model. Human-centric Computing and Information Sciences 11:01

    doi: 10.22967/HCIS.2021.11.001

    CrossRef   Google Scholar

    [76]

    Yang X, Yang X, Li Y, Zhang J, Kang Y. 2021. Obstacle avoidance in the improved social force model based on ant colony optimization during pedestrian evacuation. Physica A: Statistical Mechanics and Its Applications 583:126256

    doi: 10.1016/j.physa.2021.126256

    CrossRef   Google Scholar

    [77]

    Lu T, Zhao Y, Wu P, Zhu P. 2021. Pedestrian ascent and descent behavior characteristics during staircase evacuation under invisible conditions. Safety Science 143:105441

    doi: 10.1016/j.ssci.2021.105441

    CrossRef   Google Scholar

    [78]

    Song Y, Niu L, Liu P, Li Y. 2022. Fire hazard assessment with indoor spaces for evacuation route selection in building fire scenarios. Indoor and Built Environment 31:452−65

    doi: 10.1177%2F1420326X21997547

    CrossRef   Google Scholar

    [79]

    Xu K, Gai WM, Salhi S. 2021. Dynamic emergency route planning for major chemical accidents: Models and application. Safety Science 135:105113

    doi: 10.1016/j.ssci.2020.105113

    CrossRef   Google Scholar

    [80]

    Liu L, Zhang H, Xie J, Zhao Q. 2021. Dynamic evacuation planning on cruise ships based on an improved ant colony system (IACS). Journal of Marine Science and Engineering 9:220

    doi: 10.3390/jmse9020220

    CrossRef   Google Scholar

    [81]

    Liu Y, Du J, Sun C. 2021. Potential-based three-dimensional route choice model for pedestrian evacuation on terraced stands. Journal of Statistical Mechanics: Theory and Experiment 2021:23405

    doi: 10.1088/1742-5468/abdc14

    CrossRef   Google Scholar

    [82]

    Zhang Y, Li J, Kong D, Xing X, Luo Q, et al. 2021. Modeling and simulation of departure passenger's behavior based on an improved social force approach: A case study on an airport terminal in China. Advances in Civil Engineering 2021:6657017

    doi: 10.1155/2021/6657017

    CrossRef   Google Scholar

    [83]

    Wang J, Wei G, Dong X. 2021. A dynamic fire escape path planning method with BIM. Journal of Ambient Intelligence and Humanized Computing 12:10253−65

    doi: 10.1007/s12652-020-02794-2

    CrossRef   Google Scholar

    [84]

    Zhao Y, Liu H, Gao K. 2021. An evacuation simulation method based on an improved artificial bee colony algorithm and a social force model. Applied Intelligence 51:100−23

    doi: 10.1007/s10489-020-01711-6

    CrossRef   Google Scholar

    [85]

    Niu Y, Kong D, Zhang Y, Xiao J. 2021. Real-time evacuation strategy based on cell-inspired simulation model. IEEE Transactions on NanoBioscience 20:202−11

    doi: 10.1109/TNB.2020.3039992

    CrossRef   Google Scholar

    [86]

    Ping P, Wang K, Kong D. 2018. Analysis of emergency evacuation in an offshore platform using evacuation simulation modeling. Physica A: Statistical Mechanics and its Applications 505:601−612

    doi: 10.1016/j.physa.2018.03.081

    CrossRef   Google Scholar

    [87]

    Zhang D, Huang G, Ji C, Liu H, Tang Y. 2021. Pedestrian evacuation modeling and simulation in multi-exit scenarios. Physica A: Statistical Mechanics and its Applications 582:126272

    doi: 10.1016/j.physa.2021.126272

    CrossRef   Google Scholar

    [88]

    Ma G, Wang Y, Jiang S. 2021. Optimization of building exit layout: Combining exit decisions of evacuees. Advances in Civil Engineering 2021:6622661

    doi: 10.1155/2021/6622661

    CrossRef   Google Scholar

    [89]

    Yue H, Zhang J, Chen W, Wu X, Zhang X, et al. 2021. Simulation of the influence of spatial obstacles on evacuation pedestrian flow in walking facilities. Physica A: Statistical Mechanics and its Applications 571:125844

    doi: 10.1016/j.physa.2021.125844

    CrossRef   Google Scholar

    [90]

    Zhang Z, Jia L. 2021. Optimal guidance strategy for crowd evacuation with multiple exits: A hybrid multiscale modeling approach. Applied Mathematical Modelling 90:488−504

    doi: 10.1016/j.apm.2020.08.075

    CrossRef   Google Scholar

    [91]

    Wang W, Wan F, Lo SM. 2020. Game theory model of exit selection in pedestrian evacuation considering visual range and choice firmness. Chinese Physics B 29(8):084502

    doi: 10.1088/1674-1056/ab973a

    CrossRef   Google Scholar

    [92]

    Gao J, He J, Gong J. 2020. A simplified method to provide evacuation guidance in a multi-exit building under emergency. Physica A: Statistical Mechanics and Its Applications 545:123554

    doi: 10.1016/j.physa.2019.123554

    CrossRef   Google Scholar

    [93]

    Yang X, Yang X, Wang Q. 2020. Pedestrian evacuation under guides in a multiple-exit room via the fuzzy logic method. Communications in Nonlinear Science and Numerical Simulation 83:105138

    doi: 10.1016/j.cnsns.2019.105138

    CrossRef   Google Scholar

    [94]

    Liu T, Yang X, Wang Q, Zhou M, Xia S. 2020. A fuzzy-theory-based cellular automata model for pedestrian evacuation from a multiple-exit room. IEEE Access 8:106334−106345

    doi: 10.1109/ACCESS.2020.3000606

    CrossRef   Google Scholar

    [95]

    Cao S, Fu L, Song W. 2018. Exit selection and pedestrian movement in a room with two exits under fire emergency. Applied Mathematics and Computation 332:136−47

    doi: 10.1016/j.amc.2018.03.048

    CrossRef   Google Scholar

    [96]

    Li Y, Jia H, Li J, Gong J, Sun K. 2017. Pedestrian evacuation behavior analysis and simulation in multi-exits case. International Journal of Modern Physics C 28:1750128

    doi: 10.1142/S0129183117501285

    CrossRef   Google Scholar

    [97]

    Li J, Wang J, Li J, Wang Z, Wang Y. 2022. Research on the influence of building convex exit on crowd evacuation and its design optimization. Building Simulation 15:669−84

    doi: 10.1007/s12273-021-0858-8

    CrossRef   Google Scholar

    [98]

    Li J, Wang J, Xu S, Feng J, Li J, et al. 2022. The effect of geometric layout of exit on escape mechanism of crowd. Building Simulation 15:659−68

    doi: 10.1007/s12273-021-0799-2

    CrossRef   Google Scholar

    [99]

    Wu P, Wang Y, Jiang J, Wang J, Zhou R. 2022. Evacuation optimization of a typical multi-exit subway station: Overall partition and local railing. Simulation Modelling Practice and Theory 115:102425

    doi: 10.1016/j.simpat.2021.102425

    CrossRef   Google Scholar

    [100]

    Wang J, Sarvi M, Ma J, Haghani M, Alhawsawi A, et al. 2022. A modified universal pedestrian motion model: Revisiting pedestrian simulation with bottlenecks. Building Simulation 15:631−44

    doi: 10.1007/s12273-021-0841-4

    CrossRef   Google Scholar

    [101]

    Wang J, Li J, Li J, Feng J, Xu S, et al. 2022. Performance optimization of the obstacle to corner bottleneck under emergency evacuation. Journal of Building Engineering 45:103658

    doi: 10.1016/j.jobe.2021.103658

    CrossRef   Google Scholar

    [102]

    Li Z, Xu W. 2020. Pedestrian evacuation within limited-space buildings based on different exit design schemes. Safety Science 124:104575

    doi: 10.1016/j.ssci.2019.104575

    CrossRef   Google Scholar

    [103]

    Wang J, Jin B, Li J, Chen F, Wang Z, et al. 2019. Method for guiding crowd evacuation at exit: The buffer zone. Safety Science 118:88−95

    doi: 10.1016/j.ssci.2019.05.014

    CrossRef   Google Scholar

    [104]

    Song X, Xie H, Sun J, Han D, Cui Y, et al. 2019. Simulation of Pedestrian Rotation Dynamics Near Crowded Exits. IEEE Transactions on Intelligent Transportation Systems 20:3142−55

    doi: 10.1109/TITS.2018.2873118

    CrossRef   Google Scholar

    [105]

    Wang J, Ma J, Lin P, Chen J, Fu Z, et al. 2019. Experimental study of architectural adjustments on pedestrian flow features at bottlenecks. Journal of Statistical Mechanics: Theory and Experiment, 2019:83402

    doi: 10.1088/1742-5468/ab3190

    CrossRef   Google Scholar

    [106]

    Shi X, Ye Z, Shiwakoti N, Tang D, Lin J. 2019. Examining effect of architectural adjustment on pedestrian crowd flow at bottleneck. Physica A: Statistical Mechanics and Its Applications 522:350−64

    doi: 10.1016/j.physa.2019.01.086

    CrossRef   Google Scholar

    [107]

    Tian H, Dong L, Xue Y. 2015. Influence of the exits' configuration on evacuation process in a room without obstacle. Physica A: Statistical Mechanics and Its Applications 420:164−78

    doi: 10.1016/j.physa.2014.10.002

    CrossRef   Google Scholar

    [108]

    Wang J, Zhang L, Shi Q, Yang P, Hu X. 2015. Modeling and simulating for congestion pedestrian evacuation with panic. Physica A:Statistical Mechanics and Its Applications 428:396−409

    doi: 10.1016/j.physa.2015.01.057

    CrossRef   Google Scholar

  • Cite this article

    Shao X, Ye R, Wang J, Feng J, Wang Y, et al. 2023. Progress and prospects in crowd safety evacuation research in China. Emergency Management Science and Technology 3:1 doi: 10.48130/EMST-2023-0001
    Shao X, Ye R, Wang J, Feng J, Wang Y, et al. 2023. Progress and prospects in crowd safety evacuation research in China. Emergency Management Science and Technology 3:1 doi: 10.48130/EMST-2023-0001

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Progress and prospects in crowd safety evacuation research in China

Abstract: China has a population of 1.4 billion, ranking first in the world. With the increase in China's economic development and population, the construction of various types of buildings in China is also increasing, and associated safety hazards are gradually increasing. Therefore, it is necessary to study the safe evacuation of people inside and outside the building in emergency situations. In recent years, some scholars have used the traditional statistical method of literature review to analyze the research frontiers in the field of safety evacuation, but few scholars have used bibliometric methods to analyze and review the current situation of research in this field. Therefore, this paper adopts the analysis method combining bibliometrics and traditional literature review to summarize the research status of crowd evacuation published by Chinese scholars in the Web of Science core database, and uses VOSviewer to analyze the authors, institutions, and keywords of the literature search results, so as to identify their research hotspots. The results show that the last three years have been the peak period of crowd evacuation studies, with many disciplines involved in this field and they are closely related, led by the number of papers related to architecture. Simulation, model, behavior, among others, have been the most used keywords in this research field, and the research on path planning and exit selection behavior has also increased significantly. According to the keyword analysis, three hot spots of safety evacuation research, namely large-scale group evacuation, evacuation path planning and evacuation exit selection are analyzed in detail.

    • According to the seventh census, China ranks first in the world with a population of over 1.4 billion. Due to the large population and the increase in the number of large commercial complex buildings in China, safety hazards have increased significantly. More serious accidents due to untimely evacuation also abound. According to incomplete statistics, there have been many casualties caused in crowd evacuation in China. Some of the causes of accidents and casualties are shown in Table 1.

      Table 1.  Summary of crowd evacuation casualty accidents in China.

      TimeLocationCause of accidentNumber of casualties
      February 5, 2004Miyun County, BeijingA light show was held, a large trampling accident occurred due to crowding and trampling on the Rainbow Bridge and negligence of security personnel[1].37 people died and 37 people were injured
      December 31, 2014The Bund of ShanghaiA light show was held and someone overbalanced and there were too many people in the venue, resulting in multiple falls and subsequent crowding and trampling accidents[2].36 people died and 49 people were injured
      November 18, 2017Beijing Daxing Xhongmen TownA householder refitted a building without authorization, the personnel after the fire did not get timely evacuation, causing a fire accident[3].19 people died and 8 people were injured
      February 25, 2017Honggu Tan New District, Nanchang City, JiangxiA hotel was privately closed for renovation without the approval of relevant authorities, resulting in blocked evacuation routes. People failed to evacuate in time after a fire broke out[4].10 people died and 13 people were injured
      April 2, 2017Daguan Economic Development Zone,
      Anqing City
      A dust explosion occurred in a workshop. Due to non-compliance with the layout of the workshop and a certain exit was blocked by flammable materials, personnel did not escape in time[5].5 people died and 3
      people were injured
      May 16, 2019Changning District,
      Shanghai
      A plant collapse occurred. Due to the chaotic management of the plant site, serious casualties were ocurred[6].12 dead and 10 seriously injured
      March 7, 2020Quanzhou, Fujian ProvinceA major collapse occurred at a hotel where people were not evacuated in time due to the building's poor design[7].29 people died and 42 people were injured

      According to the survey, the study of bibliometrics around the world started in 1917. However, the first use of bibliometrics for literature research in China started in 1964[8]. Literature analysis using bibliometric methods can easily identify not only the hot spots and frontiers of research in the field of safety evacuation, but also the 'leaders' among scholars in the field[9]. At present, scholars in many fields use bibliometrics to evaluate the current status of research and the future development trends in their subject areas. Li & Zhao[10] carried out a study on environmental assessment. Sun & Grimes[11] explored the dynamic structure of Chinese emerging innovation research. In addition, literature reviews have been conducted using bibliometric methods in fields such as business economics[1214], chemistry[1517], computer science[1820], and medical sciences[2123]. However, in the field of safety evacuation, most scholars have favored traditional statistical methods of literature review to analyze the research frontiers in the field. For example, He et al.[24] reviewed the research progress of crowd psychological behavior mechanisms and crowd evacuation animation in the process of safety evacuation. Li et al.[25] reviewed the role and advantages of the cellular automata model in the study of personnel evacuation. Zhou et al.[26] reviewed the research on guidance methods and guidance techniques for crowd evacuation in emergency situations. Ding et al.[27] reviewed the recent literature on vertical evacuation of high-rise buildings. Zhu et al.[28] reviewed the research literature on the movement characteristics of pedestrians on stairs. Few scholars have used bibliometric methods to analyze and review the current state of research in the field of safety evacuation in China. Therefore, this paper adopts a combination of bibliometric and traditional literature review methods to search and count the research literature related to safety evacuation in the Web of Science core database for the 30 years from 1990 to 2021, and analyze the current research status and future development trend of this field. The results of the study can provide a reference for researchers and policy makers in the public safety field.

      The structure of this paper is as follows: the second part of the paper describes the data sources and research methods; the third part describes the results of the literature analysis, including the year of publication and number of articles, subject distribution, author distribution, journal distribution, citation analysis, and keyword co-occurrence analysis; the fourth part describes the research hotspots of safety evacuation in China; and the fifth part provides the research conclusions of this paper.

    • The Web of Science database is the world's largest online database of academic journals[29]. To ensure the accuracy and credibility of the data, the literature used in this study was obtained from the Web of Science core database. The Web of Science core database of safety evacuation was searched on December 25, 2021. The search results of the Web of Science database differed slightly from date to date because the database is continuously updated[30]. Therefore, the data on the day of the search were taken as the research sample for this study. Using 'topic' as the search term, we entered 'evacuation' in the search box and searched the database for all literature containing this term in the title, abstract, or keyword list between 1990 and 2021. A total of 23,731 documents were searched. The screening of these articles is divided into three steps. First of all, this paper intends to study the research in the field of safety evacuation in China, so by selecting 'PEOPLES R CHINA', 'CHINA', 'TAIWAN' and 'HONG KONG' in the Countries/Regions column, the relevant literature on safety evacuation research in China was refined, and the remaining 3006 papers were screened out. Then filter out articles in irrelevant fields, such as 'medicine', 'geology', and 'economics' were excluded. Finally, after carefully screening and checking, a total of 1380 documents met the search requirements of this study. It should however be emphasized that the selection of articles related to 'safety evacuation' was carried out manually by the authors. Therefore, there may be a little oversight in the number of articles. The search records included title, author, abstract, keywords, year, journal, etc.

      The types and numbers of documents retrieved are shown in Table 2. Most of the documents were Articles (1,352 articles, 97.97%), and both Meeting and Review Articles types were less than 20 documents. The total sum of the listed types of literature was 1,419, and the sum of the types of literature exceeded the number of retrieved literatures, so there were cases where the same literature belonged to multiple types.

      Table 2.  Literature category and quantity.

      No.Document typeNumber of
      literature/article
      Proportion (%)
      1Articles1,35297.97
      2Early Access201.45
      3Meeting191.38
      4Review Articles161.16
      5Others120.87
    • Bibliometrics is the study of the literature system and bibliometric characteristics. It uses mathematical, statistical and other econometric research methods to quantitatively measure the status of research and the contributions made in a field[31,32]. Therefore, this paper intends to use bibliometric methods to study the current status of research and development trends of safety evacuation from quantitative and qualitative perspectives.

      At present, the commonly used bibliometric analysis software mainly include VOSviewer and CiteSpace. VOSviewer has more advantages in large amounts of data analysis, displaying correlation strength and presenting the relationship between subject terms[33], while CiteSpace is more suitable for document analysis with small amounts of data, in this study we therefore chose VOSviewer for document analysis. VOSviewer software was used to analyze the authors, institutions, sources, and keywords of literature related to safety evacuation in China. VOSviewer software can be used to construct and view bibliometric maps, and providing the basic functions needed to visualize bibliometric networks in a relatively simple way[34]. The size of the circles in the VOSviewer network diagram indicates the level of importance. The larger the circle, the greater the importance. And the lines between the circles indicate the relatedness between research items. The closer the lines, the higher the degree of relatedness[35]. The VOSviewer software was used to visualize and analyze the literature, so as to identify the research hotspots, development trends and general characteristics of related literature in this field.

    • According to the search method introduced above, the research progress of the field in different time periods can be clearly viewed. The annual publication volume in the field of safety evacuation in China between 1990 and 2021 is shown in Fig. 1. As can be seen from Fig. 1, the overall trend of annual publications is on the rise, although the number of publications has decreased in some years. Before 2008, there were fewer related studies, and (with the exception of 2006), the number of publications in the remainder of the years did not exceed 10. 2017−2021 was the fastest growing five years in the field of safety evacuation in China, with the number of publications above 100 each year, indicating that the research enthusiasm in this field is increasing. The largest number of publications appears in 2020, with 231 publications, accounting for 16.74% of the total number of publications. It was followed by 2019, with 208 publications, accounting for 15.07% of the total number of publications. And 199 publications in 2021 rank in third place, accounting for 14.42% of the total number of publications.

      Figure 1. 

      Annual publications in the field of domestic safety evacuation during 1990−2021.

      According to the statistics of the number of publications, research related to safety evacuation in China until 2021 is divided into three phases. The first stage was from 1990 to 2007, which was named as the 'initiation stage'. The number of literature in this stage did not exceed 10 articles per year. Although the number of articles in this period was small, three of the top 10 cited papers were published in this period, and all of them were published in 2006 (see Table 3). According to the number of citations, the typical papers in this period include the following: Song et al.[36] established a 'multi-grid model' based on the social force model to study the interaction between two factors affecting evacuation; Lo et al.[37] explored the method of finding escape exits during emergency evacuation; Song et al.[38] explored the reasons for the complex behavior of people during evacuation; Yang et al.[39] developed a cellular automata model to simulate the effect of kinship behavior on evacuation efficiency during evacuation; Lo et al.[40] proposed a spatial grid evacuation model (SGEM) to simulate the pedestrian evacuation process.

      Table 3.  The top 10 cited literature of Chinese scholars in safety evacuation from 1990 to 2021.

      RankTitle of articleFirst authorSourceCitation
      rates
      Published
      year
      Address
      1Modeling crowd evacuation of a
      building based on seven methodological approaches
      Zheng XiaopingBuilding And Environment3492009Beijing Univ Chem Technol
      2Simulation of evacuation processes
      using a multi–grid model for
      pedestrian dynamics
      Song WeiguoPhysica A Statistical Mechanics And Its Applications2082006Univ Sci & Technol China
      3Static floor field and exit choice for pedestrian evacuation in rooms with internal obstacles and multiple exitsHuang HaijunPhysical Review E1982008Beijing Univ Aeronaut & Astronaut
      4Agent–based modelling and simulation
      of urban evacuation: relative
      effectiveness of simultaneous and
      staged evacuation strategies
      Chen XuweiJournal of The Operational Research Society1832008SW Texas State Univ
      5Route choice in pedestrian evacuation under conditions of good and zero visibility: Experimental and simulation resultsGuo RenyongTransportation Research Part B–Methodological1782012Inner Mongolia Univ
      6A game theory based exit selection
      model for evacuation
      Lo SiumingFire Safety Journal1642006City Univ Hong Kong
      7Agent–based evacuation model of large public buildings under fire conditionsShi JianyongAutomation in Construction1622009Shanghai Jiao Tong Univ
      8Evacuation behaviors at exit in CA
      model with force essentials: A
      comparison with social force model
      Song WeiguoPhysica A Statistical Mechanics And Its Applications1512006Univ Sci & Technol China
      9A social force evacuation model with
      the leadership effect
      Hou LeiPhysica A Statistical Mechanics And Its Applications1452014Shanghai Univ Sci
      10A dynamic evacuation network optimization problem with lane reversal and crossing elimination strategiesXie ChiTransportation Research Part B–Logistics And Transportation Review1372010Univ Texas Austin

      The second phase was from 2008 to 2016, which is named as the 'initial development phase', and the number of literature in this phase is 20-100 per year. This period has the highest number of highly cited literature publications (see Table 3). Based on the number of citations, some typical papers in this period include the following: Zheng et al.[41] analyzed the advantages and disadvantages of seven crowd evacuation models including the cellular automata model; Huang & Guo[42] designed a modified floor field model to simulate pedestrian evacuation in rooms with internal obstacles and multiple exits; Guo et al.[43] studied the pedestrian evacuation path selection problem under good and zero visibility conditions; Shi et al.[44] proposed a system simulation model to simulate the evacuation process of people in a fire situation; Hou et al.[45] investigated the effect of the number and location of leaders on the evacuation efficiency.

      The third phase is from 2017 to 2021, which is named as 'high speed development phase', and the number of papers in this phase is more than 100 per year. In this period, a large number of scholars in China have joined the research field of safety evacuation, so the number of literature exceeds 200 in 2019 and 2020. Among the literature with high numbers of citations, the more typical ones include: Liu et al.[46] proposes a novel emergency evacuation path planning method combining the Extended Social Force Model (ESFM) and the Improved Artificial Bee Colony (IABC) algorithm, this paper has been cited 143 times. Liu et al.[47] established a crowd evacuation simulation approach that is based on navigation knowledge and two-layer control mechanism; Lu et al.[48] studied the influence of group for on personnel evacuation; Zhao et al.[49] study the impact of different obstacle shapes and distance from exit locations on evacuation efficiency; Chen et al.[50] study the collision avoidance behavior of pedestrians in two-exit classrooms during evacuation through a cellular automata model; Liu et al.[51] proposes a video data-driven social force model for simulating crowd evacuation.

    • The discipline distribution of the research literature is to understand the distribution of different disciplines in the field of safety evacuation research and to explore the leading disciplines in this field. By looking at the 'Analyze Results' of the Web of Science core database, we can see that there are 56 categories of disciplines involved in this field, among which 15 categories contain only one article and six categories contain only two articles.

      In this study, the number of relevant articles in each discipline were counted, and the hot disciplines in the field were investigated according to the ranking of the literature volume. The top 10 discipline categories in terms of literature volume and the number of publications are shown in Table 4. The sum of the volume of each discipline category in the table exceeds the sum of the retrieved literature, indicating that the disciplines are not independent of each other, and a piece of literature may be involved in more than one discipline. From Table 4, we can see that the top 10 disciplines in terms of volume are Engineering, Physics, Computer Science, Transportation, Operations Research Management Science, Mathematics, Construction Building Technology, Science Technology Other Topics, Environmental Sciences Ecology, and Materials Science. The leading discipline in this field is Engineering, with 542 articles, accounting for 39.275% of the total number of articles. This is followed by Physics (349 articles, 25.290%). The third is Computer Science (303 articles, 21.957%). Literature review shows that evacuation studies are mostly concentrated in buildings, such as super high-rise buildings, underground multi-story buildings, etc. Moreover, the research on the dynamics of crowd evacuation behavior is usually biased toward physical modeling, so Engineering and Physics disciplines are the two disciplines with the largest number of articles. Computer Science is also on the list, indicating that computer technology is increasingly being used in the study of safety evacuation, and intelligent evacuation tools are being explored and gradually applied.

      Table 4.  Statistics on the distribution of the top 10 disciplines in the literature related to the field of safety evacuation in China during the period 1990−2021.

      RankSubject categoryNumber of
      publications
      Percentage of total
      publications (%)
      1Engineering54239.275
      2Physics34925.290
      3Computer Science30321.957
      4Transportation14310.362
      5Operations Research Management Science1128.116
      6Mathematics1037.464
      7Construction Building Technology977.029
      8Science Techology Other Topics836.014
      9Environmental Sciences Ecology805.797
      10Materials Science735.290
    • Finding the distribution of authors of the literature helps to understand the important contributions of the authors in the field. The retrieved literature was written by more than 200 different authors, and the top 10 authors of the published literature were counted, and the statistical results are shown in Fig. 2. The authors of the literature were clustered and analyzed by VOSviewer to obtain a collaborative network view of the authors related to safety evacuation, as shown in Fig. 3, where the colors in the figure represent collaborative clusters (groups), which can identify the highly productive authors in the field, as well as the collaborative relationships among the authors. It is worth noting that the literature search results in the Web of Science database cannot distinguish between authors with the same name, so the author searched the literature manually in order to filter the authors with the same name and the same institution as the same author.

      Figure 2. 

      Statistics of the top 10 authors in the number of publications in the field of safety evacuation Web of Science from 1990 to 2021.

      Figure 3. 

      Network diagram of researchers in the field of safe evacuation from 1990 to 2021.

      The author with the highest number of publications is Song Weiguo (Univ Sci & Technol China, 22%), who has published work in 27 journals. The next highest author is Lo Siuming (City Univ Hong Kong, 14%), and it is noteworthy that the two scholars have co-authored more than 10 publications. In addition, many of the papers are co-authored by multiple authors. For example, Song Weiguo & Zhang Jun co-authored in 2021: Where luggage-related facilities should be placed along passageways in traffic hubs: right, left, or in the middle?[52]; Yang Lizhong & Fu Zhijian co-authored in 2018: Update schemes of multi-velocity floor field cellular automatization for pedestrian dynamics[31]; Ma Jian & Lo Siuming co-authored: Pedestrian ascent and descent fundamental diagram in 2017[53]. Figure 3 also shows that the main research scholar in this field is Song Weiguo. According to the color division of the network diagram, the authors can be roughly divided into 11 groups, indicating that scholars studying safety evacuation in China are closely connected with each other, and mostly choose to conduct research through teamwork.

      In addition, most of the scholars in the field of safety evacuation conduct their research within universities, and therefore most of the institutions to which the published related articles belong are universities. Further analysis of the research institutions of the safety evacuation-related literature in China using VOSviewer software helps to understand the leading institutions in the field. Statistics on the number of articles issued by each institution are shown in Table 5 (taking the top 10). There are three institutions with more than 100 articles, namely University of Science and Technology of China (149 articles), Beijing Jiaotong University (109 articles), and Tsinghua University (107 articles). So these three institutions are leading the way in this field.

      Table 5.  Statistics on the number of articles issued by each institution.

      RankLiterature research institutionNumber of publications
      1University of Science and Technology of China149
      2Beijing Jiaotong University109
      3Tsinghua University107
      4City University of Hong Kong78
      5Southwest Jiaotong University67
      6Wuhan University of Technology50
      7Tongji University48
      8Chinese Academy of Sciences41
      9Southeast University38
      10Beihang University38
    • The search yielded 1,380 papers from about 270 journals, of which 130 journals published only one paper in the field of safety evacuation and 39 journals published two related papers. The core journals in this field can be derived through law of Bradford, and the formula for calculating the number of Bradford core journals was proposed by the Belgian scholar L. Egghe[51] , that is, r0 = 2ln(eE × Y), where E is a constant value of 0.5772, and Y denotes the number of papers in the journals with the largest amount of literature, which is 172 in this paper, and is brought in to obtain the number of core journals of about 11 papers. VOSviewer software was used to draw the journal co-occurrence network diagram, as shown in Fig. 4. The information of core journals is shown in Table 6. The analysis shows that the journal Physica A- Statistical Mechanics And Its Applications has the highest number of publications with 172 articles, accounting for 12.5% of the total literature, and is the most prolific journal in this field. The next most prolific journal is Safety Science (80 articles, 5.8%). Third in the list is the IEEE Access journal (42 articles, 3.0%). The complex of connecting lines between the circles in the Fig. 4 indicates that the journals are closely linked and are citing each other.

      Figure 4. 

      Network diagram of relevant journals in the field of safety evacuation.

      Table 6.  Information of core journals in the field of safety evacuation.

      RankJournal nameNumber of articlesPercentage
      of total
      publications (%)
      Impact factor*
      1Physica A Statistical Mechanics and Its Applications17212.464%3.295
      2Safety Science805.797%5.16
      3IEEE Access423.043%4.983
      4Mathematical Problems in Engineering372.681%1.125
      5International Journal of Modern Physics C362.609%1.453
      6Simulation Modelling Practice and Theory312.246%3.336
      7Sustainability302.174%2.966
      8Chinese Physics B292.101%1.265
      9Journal of Statistical Mechanics Theory and Experiment282.029%1.425
      10Fire Safety Journal271.957%2.802
      11IEEE Transactions on Intelligent Transportation Systems241.739%8.632
      * Impact factor taken from 2021
    • The number of citations reflects the recognition and influence of the literature in its field, as well as the current research hotspots and trends in the field. Among the 1,380 documents retrieved, 22 documents were cited more than 100 times and two documents were cited more than 200 times. Table 3 summarizes the top 10 cited literature in the field of safety evacuation during the period 1990–2021. From Table 3, it can be seen that most of the top 10 cited articles are from before 2010. And combined with the analysis of the number of publications above, it can be seen that the number of citations is higher before 2010 although the number of publications is lower. The most cited literature is the review paper by Zheng et al. Modeling crowd evacuation of a building based on seven methodological approaches published in Building And Environment in 2009[41]. The article describes seven approaches to studying crowd evacuation in buildings and discusses the advantages and disadvantages of each. Later scholars cited this literature to explore: a modified approach to pedestrian dynamics that allows for crowd dynamics guidance[54]; a novel social force model describing pedestrian movement on stairs and evacuation dynamics[55]; the effect of building environment and evacuation behavior on evacuation time[56].

      The second most cited is: Simulation of evacuation processes using a multi–grid model for pedestrian dynamics published in 2006 in the journal Physica A - Statistical Mechanics And Its Applications, written by Song et al.[36]. This article analyzed the rules of interactions among pedestrians or pedestrians and constructions and the influences of interaction forces and drift on evacuation time. Later scholars carried out research on the relationship between microscopic features of pedestrian dynamics based on this paper[57], and novel meta-automata models considering heterogeneous behavior of pedestrians[58].

      The third is Static floor field and exit choice for pedestrian evacuation in rooms with internal obstacles and multiple exits[42], published in Journal of Physical Review E. In this article, a modified floor field model is proposed to simulate pedestrian evacuation in rooms with internal obstacles and multiple exits, and employing a logit-based discrete choice principle to govern the exit selection. Later scholars cited this literature to study: pedestrian path selection behavior during evacuation in indoor areas with obstacles[59]; pedestrian evacuation dynamics affected by fire spread[60].

      It is worth noting that among the top 10 cited papers, two papers are from Song and three papers are from the journal Physica A Statistical Mechanics And Its Applications.

      In addition, co-citation analysis of the relevant literature is considered in this paper. Based on the Minimum number of citations of a cited reference = 50, 50 literature records satisfying the threshold value are selected from 24,818 references to generate a visual network mapping of the co-citation analysis of the literature (as shown in Fig. 5). In the co-citation analysis network of the literature, the size of the nodes reflects the total frequency of citations of a particular literature, i.e., the higher the number of citations, the larger the nodes[61]. From Fig. 5, the top two cited articles are all from the authors Helbing et al[62], who wrote Simulating dynamical features of escape panic in 2000 and Social force model for papers in 1995. The third is the paper Simulation of pedestrian dynamics using a two-dimensional cellular automation by Burstedde et al.[63].

      Figure 5. 

      The network diagram of the co-citation analysis of the relevant literature.

    • Keywords are conceptual words extracted by authors from the text to describe their research in a concise way. The analysis of keywords can help with understanding the research hotspots and future development trends in related fields, which is the core content of this study, and it is also one of the important ways to effectively search literature. The keyword analysis method in Callon et al. From translations to problematic networks: An introduction to co-word analysis[64] has been widely cited. In this paper, VOSviewer software was used to conduct keyword analysis on 1,380 retrieved articles and draw the network diagram of literature keyword co-occurrence, as shown in Fig. 6. In the total of 4,261 keywords, those with more than 20 occurrences were recorded, and a total of 70 keywords met the requirements. The connecting lines between the circles in Fig. 6 indicate the relevance of the keywords, indicating that the keywords are closely connected with each other. The keywords in Fig. 6 are roughly divided into four groups by color, and the keywords in the same group usually have closer relationships[65]. Words such as simulation, behavior, cellular automata are a cluster, such as shown by Dang et al.[66] who explored a virtual reality large-scale crowd evacuation chain navigation grid based on meta-cellular automata. Model, time, emergency evacuation are a cluster, e.g., Wang et al.[67] explored a subway station emergency evacuation model considering personality traits. Flow, social force mode, pedestrians are a cluster, such as Wang & Cao[68] studied a simulation model of pedestrian evacuation strategy under limited visibility. Movement, crowd, speed are a cluster, e.g., Huang et al.[69] studied an experiment on the evacuation behavior of passengers in high-rise deck buses.

      Figure 6. 

      Literature keyword co-occurrence network from 1990 to 2021.

      The keywords with high frequency are simulation, evacuation, model, behavior, dynamics, flow, social force model, pedestrian evacuation, emergency evacuation, and pedestrian dynamics. This indicates that the current research in the field of safety evacuation in China is mainly focused on these hot spots. The term 'simulation' appears most frequently, which indicates that model simulation is more widely studied in the field of safety evacuation in China. In addition, the study of pedestrian dynamics is also more common.

      The keywords in different years also have obvious differences. According to the analysis of the year of publication and the number of articles above, keyword co-occurrence analysis was conducted in three phases using VOSviewer software, and the keyword co-occurrence network diagram is shown in Fig. 7. From Fig. 7, the hot keywords in the first stage (1990–2007) are jamming transition, cellular automata; simulation, computer, and evacuation model. The hot keywords in the second stage (2008–2016) are behavior, dynamics, flow, model, and cellular automata. And the hot keywords in the third phase (2017–2021) are simulation, flow, exit choice, route choice, and fire. The hot keywords in the different stages are shown in Table 7.

      Figure 7. 

      Co-occurrence network of literature keywords at each stage: (a) the first stage; (b) the second stage; (c) the third stage.

      Table 7.  Hot keywords in different stages.

      No.1990–20072008–20162017–20211990–2021
      1simulationsimulationsimulationsimulation
      2firemodelbehaviorevacuation
      3modelbehaviormodelmodel
      4computerdynamicsevacuationbehavior
      5jamming transitionflowdynamicsdynamics
      6pedestrian dynamicsevacuationflowflow
      7cellular automatacellular-automata modesocial force modelsocial force model
      8pedestrian flowsocial force modelpedestrian evacuationpedestrian evacuation
      9evacuationpedestrian dynamicsoptimizationemergency evacuation
      10occupant evacuationjamming transitionemergency evacuationpedestrian dynamics

      When comparing the hot keywords in the three stages, it is found that the hot keywords in each stage have not changed much. The simulation study has been the hot method of safety evacuation research in China, steadily appearing in the first place. Compared with the first stage, the study of pedestrian behavior in the second and third stages gradually becomes a hot spot. In Fig. 7, it can be seen that in addition to the hot keywords, the research on the selection of paths and exits has also increased significantly in the third stage, where the research combined with optimization, i.e., the optimal evacuation path selection under fire situations, is also increasing. It can be seen that with the development of economy and technology in China, the number of high-rise buildings and large integrated commercial buildings is gradually increasing, and the resulting safety accidents are also increasing, so people's attention to the safe evacuation after fire is also increasing, and the research hotspots are gradually shifting to the selection of optimal escape paths.

      In the next few years, with the increase of large underground commercial complexes in China, the research of safety evacuation may shift from above-ground buildings to underground buildings. The evacuation of people in underground shopping malls may become a new hot issue. In addition, studies on the safe evacuation of people often requires the organization of large crowds for experiments, whereas the experimental costs are large and there are more uncertainties during experiments. Therefore, in the field of evacuation research, the most used method is computer simulation. With the rapid development of intelligent technology in China in recent years, intelligent evacuation tools are also being gradually explored and applied. In summary, the trends in the field of evacuation of people are mainly focused on the 'modification of evacuation models' and the 'evacuation behavior of pedestrians'. Among them, the combination with 'fire', 'optimization' and 'emergency management' is also becoming a research trend.

    • According to the keyword analysis, it can be seen that the keywords 'simulation' and 'model' appear more frequently, so the research of crowd evacuation through model simulation has been the research hotspot in the field of safety evacuation in China. In the second and third stages, the keyword 'behavior' appears more frequently, so the study of pedestrian behavior gradually becomes a hot spot. In view of this research hotspot, the following analysis will focus on the research on crowd behavior of large-scale group evacuation. In the third stage, there is a significant increase in the research on crowd path and exit selection behavior, in which the research combined with 'optimization', i.e., the optimal evacuation path selection of crowds under fire situations, is also significantly increased. In response to this research hotspot, the following part will summarize the research on path planning during crowd evacuation and the optimization of exit bottlenecks. In summary, the following research hotspots will be specifically reviewed related to three aspects: first, research on large-scale mass crowd evacuation; second, research on path planning during crowd evacuation; and third, research on optimal design of evacuation exits.

    • The behavior of crowds in emergency situations is complex and stochastic, so scholars have paid particular attention to the uncertainty in the evacuation process of pedestrians. The specific description of the research methods and the findings of the study can be found in Table 8. In the study of large-scale group evacuation behavior, Wang et al. proposed a method to qualitatively simulate panic propagation in mass crowd evacuation, and established a simulation model of panic behavior based on system dynamics[70], to study the uncertainties affecting mass evacuation from the perspectives of efficiency and risk[71]. Cui et al.[72] analyzed the behavioral characteristics of large event audience groups and proposed a large-scale group evacuation method for large events. Zhan et al.[73] studied the path selection model for large-scale typhoon-resistant crowd evacuation in an uncertain environment under typhoon disaster. Ma et al.[74] proposed a large crowd evacuation method based on RFID (radio frequency identification) mutation theory for large crowds in cultural museums. Mei et al.[75] proposed a simulation method using the entangled emotional model (EEM) to deal with the gathering phenomenon and group collision problem during large-scale crowd evacuation.

      Table 8.  Specific analysis of the cited literature on mass crowd evacuation.

      Author, yearPanicModelAlgorithmMeasured variablesMain research contents
      Wang, 2012The numbers evacuated; correct rate of evacuation direction; speed; human trafficThe model reproduces a well-known phenomenon in crowd evacuation, namely fast is slow, and confirms that the severity of disaster exponentially positively correlates with the panic spread, and the effectiveness of rescue guidance is influenced by the leading emotion in the crowds as a whole.
      Wang, 2013DensityThe effectiveness of rescue strategies was found to be strongly related to crowd density. The higher the crowd density, the larger the minimum number of passageways for effective evacuation will be.
      Cui, 2016This paper proposes an audience behavior rehearsal and simulation system that can be applied to the real activity. The system can realize the behavior planning of the audience in the early period of large-scale organization and modularize the organization flow.
      Zhan, 2019TimeA route selection model for anti-typhoon crowd evacuation vehicles was built. The vehicle road impedance coefficient was used to embody the abilities of different vehicles in executing evacuation tasks. And the proposed method can provide emergency decision makers with a scientific and reasonable route selection scheme for anti-typhoon crowd evacuation vehicles.
      Ma, 2020Density; speedThis paper proposes a large-scale crowd evacuation method based on the mutation theory of RFID. The advantage of this algorithm is that it can overcome the contradiction between the prediction accuracy and the tracking speed, and the accuracy of the algorithm to predict the flow of large-scale people is improved, making the evacuation model more relevant to the actual situation.
      Mei, 2020Time; density; human trafficThis paper proposes a particle model, and the simulation method of the entangled emotional model (EEM) is used to deal with the gathering phenomenon and group collisions in the evacuation process. The model simulates the crowd’s kinship by forming multiple entangled pairs, which can form multiple motion clusters for a large number of people.

      In a word, research on mass crowd evacuation is becoming more and more concerned with the quantification of crowd psychological and behavioral characteristics under the influence of emergency complexity scenes. It is the choice of many scholars to add the study of panic psychology to the study of mass evacuation. They determine the law or phenomenon of large-scale evacuation, such as 'fast is slow', by studying variables such as human flow, evacuation time, speed, and density. At the same time, by means of computer simulation and algorithms, these studies can reproduce large-scale crowd evacuation processes and provide data reference for the evacuation decision from the angle of efficiency and risk. Some typical large-scale evacuation models are shown in Fig. 8.

      Figure 8. 

      Schematic diagram of a large-scale evacuation model. Reprinted from Ma et al. & Yang et al.[71,72].

    • When an emergency occurs in a complex building, it is difficult for people to choose a suitable evacuation route according to the dynamic changes of evacuation situation due to panic and unfamiliarity with the environment. Scientific and reasonable planning of pedestrian evacuation paths can effectively improve evacuation efficiency, so the research on pedestrian evacuation path planning has increased significantly in recent years. A full list of the analyses identified in this work can be found in Table 9. Yang et al.[76] used an ant colony optimization algorithm to navigate pedestrian evacuation paths with complete information, and concluded that pedestrians with complete information are able to choose shorter evacuation paths. Lu et al.[77] investigated the path selection behavior of pedestrians going up and down stairs in the absence of visibility. Song et al.[78] proposed an evacuation path selection algorithm considering hazard and time factors. Xu et al.[79] proposed an improved Dijkstra algorithm to study the dynamic multi-objective path planning problem. Liu et al.[80] proposed an improved artificial bee colony algorithm (IACS) to solve the evacuation path planning problem on cruise ships. Liu et al.[81] proposed a potential-based three-dimensional cellular automata model to describe the route choice behavior of pedestrians while evacuating terraced stands. Zhang et al.[82] built a two-story airport terminal based on a social force model to describe the path selection behavior of passengers. Wang et al.[83] proposes a BIM-based method for real-time dynamic escape path prediction analysis of people for crowd escape path planning. Zhao et al.[84] proposes a new evacuation simulation method which combines an improved artificial bee colony algorithm for dynamic path planning and SFM for simulating the movement of pedestrians, to providing pedestrians with timely route selection. Niu et al.[85] proposed a real-time evacuation strategy based on a comprehensive route constraint according to the Intelligent Decision P System (IDPS). Ping et al.[86] studied the problem of evacuation path selection for the crew of offshore platforms.

      Table 9.  Specific analysis of the cited literature in evacuation path planning.

      Author, YearExperimentModelAlgorithmVisibilityObstaclesMain research content
      Yang, 2021This paper proposes an obstacle avoidance method in the microscopic SFM, which emphasizes the solution of choosing which obstacle to detour and which side to detour in the multiple obstacle scene. Herding behavior, individual preference affected by obstacles and walls are taken into consideration when defining the desired direction of pedestrians with local information in this algorithm.
      Lu, 2021This paper carries out a series of pedestrian evacuation experiments on a staircase for both ascent and descent based on video tracking technology to extract the trajectories of pedestrians. Pedestrians tend to use the enclosure for help when ascending and descending without visibility, and offset angle is correlated with pedestrians’ route-choice behavior. These studies are helpful to understand pedestrian evacuation characteristics on stairs without visibility.
      Song, 2021By combining GIS and a fire hazard assessment method for indoor spaces, a new evacuation route selection approach that considers hazards and time is proposed in this paper.
      Xu, 2021This paper constructs a multi-indicator emergency risk assessment method that considers the evacuation speed of different population types and health consequences caused by various risk components. Then he proposes a modification of the well-known Dijkstra algorithm to deal with the problem for emergency route selection under the real effect of disaster extension. The proposed model provides reliable and practical emergency route planning services for various personnel types under different accident scenarios.
      Liu, 2021This study uses an IACS to analyze the multi-path dynamic planning of emergency evacuations on cruise ships. And the ACS is combined with the increasing flow method to improve the evacuation efficiency.
      Liu, 2021A potential-based three-dimensional route choice model for pedestrian evacuation on terraced stands is proposed. The proposed potential field algorithm reflects the influence on route choice behavior of heterogeneous heights, route distance, pedestrian congestion, and route capacity.
      Zhang, 2021A double-level model was established to describe passengers’ path planning behaviors. The avoiding force model including common avoiding force and additional horizontal avoiding force was established, and the route and node choice models were established to describe pass engers’ path planning in long-range space.
      Wang, 2020This paper proposes a real-time dynamic fire escape path prediction analysis method with BIM, and designs single and multi-person escape route planning method. The shortest path is planned by Dijkstra algorithm.
      Zhao, 2020This paper proposes a new crowd evacuation simulation method. The proposed MABCM algorithm can effectively improve the performance of ABC, and the method balances distance and congestion and shortens evacuation time to a certain extent.
      Niu, 2020This work proposes a real-time evacuation strategy. Experiments are conducted to simulate five different scenarios in a fire evacuation. The evacuation strategy with a comprehensive route constraint has a significant improvement in the evacuation efficiency and has higher robustness.
      Ping, 2018To quantify the influence of evacuation route selection on crew evacuation efficiency, two scenarios are considered. It is reasonable to prescribe the evacuation routes in advance.

      Obviously, current research on path selection is often carried out at the fire scene, and the research on visibility and obstacles is mostly related to it. Regarding the research on path planning, most of the documents included in the Web of Science database are the research on path planning models. Scholars use some algorithms to develop models and make corresponding algorithm flow charts or evacuation path planning flow charts, some of the more typical flowcharts are shown in Fig. 9. The model is combined with the algorithm to carry out relevant crowd evacuation simulation research. Therefore, the new model is compared with the existing model, and the advantages and disadvantages of the model are proposed. In this part of the study, Ant colony algorithm and Dijkstra algorithm are commonly used algorithms; cellular automata model and the Social Force Model are the basis for building various innovative models. In addition, the acquisition of pedestrian motion trajectory in the experiment is carried out by video tracking technology. In addition, the research in this aspect is increasingly combined with intelligent algorithms, showing obvious interdisciplinary characteristics.

      Figure 9. 

      Evacuation algorithm flow chart or evacuation path planning flow chart. Reprinted fromSong et al. & Xu et al. [75,76]

    • Evacuation exits are very important in conventional buildings, and there is usually more than one exit in a large building, so how to use them reasonably for effective evacuation in emergency situations is becoming an important topic, and most scholars have studied the evacuation of planar exits in buildings. A full list of the analyses identified in this work can be found in Table 10. Zhang et al.[87] proposed a pedestrian multiple exit selection model based on a continuous model. Ma et al.[88] developed a pedestrian dynamic exit decision model considering people's exit selection strategies based on a social force model. Yue et al.[89] improves the cellular automata model to study the influence of classroom obstacles on personnel evacuation path selection. Zhang & Jia[90] studied a large-scale group evacuation strategy guidance model, which generates leader location and exit selection options. Wang et al.[91] integrated game theory into a cellular automata simulation framework to study the pedestrian evacuation exit selection mechanism. Gao et al.[92] proposed a modified cellular automata model based on Floor Field theory to study the effect of different exit weight coefficients on evacuation efficiency. Yang et al.[93] proposes a cellular automata model based on fuzzy logic method for simulating the evacuation of pedestrians from a multiple-exit room. Liu et al.[94] proposed a cellular automata model based on fuzzy logic approach to study the exit selection problem during pedestrian evacuation. Cao et al.[95] proposed an extended multi-grid model to study the exit selection problem of people in a two-exit room under fire situation. Li et al.[96] developed an exit selection model considering pedestrian evacuation preferences based on a meta-cellular automata model.

      Table 10.  Specific analysis of the cited literature regarding planar exits.

      Author, YearModelAlgorithmLeaderObstaclesObject of studyMain research content
      Zhang, 2021Distance from a pedestrian to an exit; Pedestrian density
      near an exit; Exit width
      This paper proposes a multi-exit evacuation model based on a continuous model. And the model takes into account the distance between pedestrians and exits, the pedestrian density near exits, and the width of exits. The model can reproduce the phenomenon of pedestrian congestion and exit congestion, and improve the evacuation efficiency as well as utilization rate of exits significantly.
      Ma, 2021Exit quantity; Exit positionA dynamic exit decision model (EDM) is proposed to simulate decisions of evacuees in the multi-exit evacuation. The model can accurately evaluate the evacuation efficiency of different multi-exit layouts and optimize the design rules.
      Yue, 2021An exit with a prepositive obstacleIn this paper, a retardation coefficient is introduced to describe the effect of obstacles slowing down pedestrian movement. A special technique is adopted to calculate the shortest estimated distance from cell site to exit considering obstacle layout and retardation coefficient. The repulsion and isolation effect of obstacles on pedestrian flow is manifested by the clusters of evacuation path chains.
      Zhang, 2021Position of leader; Number of leaders;
      Exit selection strategy
      A simulation algorithm is proposed to integrate a pedestrian following model and strategic guidance model based on the follower-leader interaction. The guidance strategy can realize the full use of guidance capacity, information confusion reduction and uniform exit usage, all of which contribute to a reduction in evacuation time.
      Wang, 2020Visual radius; Initial crowd distribution; exit layout;By integrating game theory into a cellular automata simulation framework, the pedestrian exit choice mechanism is explicitly modeled in this paper. The model is used to study the visual radius and choice firmness of a pedestrian, initial crowd distribution of the room, exit layout as well as exit width.
      Gao, 2020Exit quantity; Exit width; Distribution of pedestriansIn this paper, A modified cellular automata model based on Floor Field theory is proposed to solve the problem of congestion in front of exits caused by the asymmetrical layout of exits or pedestrians in a multi-exit building.
      Yang, 2020The limited visibility and guide quantity; Export position; Exit widthThis paper chooses the fuzzy logic theory to investigate the problems of guide selection by informed followers and exit selection by guides. Guide’s normalized distance to the exit and the normalized density around the exit are chosen as the input variables of the fuzzy inference system to assist in deciding which exit to choose for guides.
      Liu, 2020Exit quantity; Exit width; Export position; Obstacle attributesThis paper proposes a cellular automata model based on fuzzy logic method for simulating the evacuation of pedestrians from a multiple-exit room. The combination of the output variable of fuzzy logic, exit width and herding behavior can effectively determine the target exit and solve the position conflict among pedestrians.
      Cao, 2018The effect of utility threshold
      on evacuation, active
      occupant on evacuation
      The exit selection based on random utility theory, as well as the pedestrian movement in fire, is investigated. The effects of different occupant types, the utility threshold, heat release rate of fire, burning materials and pre-movement time on evacuation are discussed.
      Li, 2017Exit widthBased on estimated evacuation time and shortest distance, pedestrian exit choice model is established considering pedestrian preference.

      Combined with computer simulations, study on the rational allocation of multiple exits within a building has been closely linked to the evacuation path planning study in the previous section. In the study of the model, scholars will include the drawn model framework diagram in the text, and some of the typical framework diagrams are shown in Fig. 10. In this part of the study, cellular automata model and social force model remain the most commonly used models. In addition, continuous model and pedestrian cell transport model are also included. Game theory, fuzzy logic theory, and random utility theory are all involved in the study of the models. During the simulation, most scholars choose to use Moore neighborhood to calculate the probability of pedestrians choosing different exits, as shown in Fig. 11. Moreover, this part of the research is more combined with leaders and obstacles. Exit width, quantity, position, etc. are the research hotspots in this section.

      Figure 10. 

      Model frame diagram. Reprinted from Ma et al. & Yue et al. [85,86].

      Figure 11. 

      Moore neighborhood. Reprinted from Zhang & Jia, Liu et al. & Cao et al. [87,91,92].

    • Crowding of pedestrians at the exits is a common phenomenon during crowd evacuation, and serious congestion may cause serious trampling accidents. Therefore, in recent years, some scholars have started to consider the special exit bottleneck problem, and the research on the structural optimization of the bottleneck exit has improved significantly. A full list of the analyses identified in this work can be found in Table 11. Li et al.[97] studied the influence of geometric structure characteristics of the convex exit on crowd evacuation, and showed that the convex exit structure is more conducive to crowd evacuation in emergency situations. Li et al.[98] studied the effect of exit position and corner exit form on crowd evacuation. Wu et al.[99] investigated the utilization of different exits in subway stations and the optimization of congestion at bottlenecks. Wang et al.[100] studied pedestrian flow at narrow exits and explored the effects of exit location, bottleneck length, and obstacles on evacuation efficiency. Wang et al.[101] studied the effect of adding obstacles of different sizes and locations in front of 30° angle exits on evacuation. Li et al.[102] studied the effect of exit design with internal and external doors and different exit widths on evacuation efficiency. Wang et al.[103] studied the effect of buffer zones before evacuation exits on evacuation efficiency. Song et al.[104] proposed the active rotation torque (ART) model that can simulate both non-competitive and competitive pedestrian behaviors near exit bottlenecks. Wang et al.[105] studied pedestrian flow characteristics at exit bottlenecks considering different door sizes and locations. Shi et al.[106] investigated the effect of different exit configurations on pedestrian flow exit performance under normal and slow pedestrian flow conditions. Tian et al.[107] studied the influence of different exit widths and positions of rooms without obstacles on evacuation efficiency. Wang et al.[108] proposed a new multi-agent based congestion evacuation model incorporating panic behavior, and studied the phenomenon of people gathering in front of exits in panic situations by simulations.

      Table 11.  Specific analysis of the cited literature on non-planar exits.

      Author, YearModelAlgorithmExperimentObject of studyMain research content
      Li, 2022The convex exit structureUsing social force model-based software, MassMotion, this paper studies the influence of geometric structure characteristics of the convex exit on crowd evacuation and put forward the optimal design strategy of this structure, so as to improve the efficiency of evacuation in an emergency.
      Li, 2022The evacuation efficiency of the 30° corner exitIn this paper, Massmotion based on social force model is used to carry out a numerical simulation on exit position and corner exit form to find out the mechanism and influence law of the slight architectural adjustment on the flow at bottleneck. The 30° angle may be a more appropriate corner exit option. In this layout, pedestrian walking direction changes less and the steering angle is smaller.
      Wu, 2022Railings at evacuation exitsTo alleviate the congestion of the evacuation in a largescale and multifunctional subway station, the utilization of different exits and the optimization of congestion at bottlenecks were investigated in this study. When the number of exits in the divided area is large, setting railings can alleviate the congestion at the exit.
      Wang, 2022The exit location; the bottleneck length; an obstacle near an exitThis paper studies pedestrian flow at narrow exits and explored the effects of exit location, bottleneck length, and obstacles on evacuation efficiency. With the increasing of bottleneck length, pedestrian flow efficiency gradually decreases. Placing an obstacle near exits in an emergency may not make the evacuation worse.
      Wang, 2022Corner exit; the size
      and location of the
      obstacle
      This paper studies the effect of adding obstacles of different sizes and locations in front of 30° angle exits on evacuation. The distance from the obstacle to the exit has the greatest influence on evacuation. At the short distance, the length of the obstacle can be increased to shorten the evacuation time.
      Li, 2020Different exit widths
      and operating doors
      Considering the differences in the individual characteristics of pedestrians and the influence factors of buildings, we proposed a safety evacuation model for limited spaces. Evacuation efficiency, bottleneck area density, escape route characteristics, and similar factors were analyzed on the basis of different exit widths and operating doors. When the exit widths are 1.0, 1.1, 1.8 and 1.9 m, the exit crowd and average densities are at their lowest.
      Wang, 2019Exit buffer zoneIn this paper, a tentative experiment was designed to preliminarily reveal the role of buffer zone in crowd evacuation. Then a social force based simulation model was established by Massmotion according to the properties of the experiment. The longer the buffer zone, the faster the agents can escape.
      Song, 2018Non-competitive and competitive pedestrian behaviors near exit bottlenecksActive rotation torque is proposed to model the active rotation behavior of pedestrians turning their torsos in the desired direction. A three-circle model is adopted to represent the shape of pedestrians to study the phenomenon of people actively squeezing to pass through an exit. The torque model can be applied to manifold scenarios with various door widths and different safety separation belt settings. And the model can simulate both non-competitive and competitive pedestrian behaviors near exit bottlenecks more accurately than the circular social force model.
      Wang, 2019Pedestrian flow features at bottlenecks, i.e. room exitsIn this paper, pedestrian flow features at bottlenecks are investigated with human-experiments considering varying door sizes and locations. The time lapses between two successive pedestrians displayed heavy-tailed distribution. In narrow door scenarios, the specific capacity was continuously decreased from the middle exit scenarios to the corner exit scenarios.
      Shi, 2019Different exit locations and obstacles near exitThis study aims to examine the effect of different geometrical layouts at the exit towards the pedestrian flow via controlled laboratory experiments with human participants. Corner exit performed better than middle exit under same obstacle condition. the effectiveness of obstacle is sensitive to its size and distance from the exit.
      Tian, 2015Different widths and positions of the exitsIn this paper, we proposed an improved and simple method to calculate the floor field. In our method, the pedestrians are treated as the movable obstacles which will increase the value of the floor field. The additional value is interpreted as the blocking effect of preceding pedestrians.
      Wang, 2015Pedestrian congestion behavior at the exitA new multi-agent based congestion evacuation model incorporating panic behavior is proposed in this paper. Pedestrians in this model are divided into four classes and each pedestrian’s status can be either normal, being overtaken, or casualty. The agents gather in front of the exits and present arched shapes close to the exits. Under the panic state the agents cohere closely and almost do not change the target exit. If there are obstacles, the congestion can be alleviated.

      In conclusion, the study of special exit bottlenecks is often combined with the study of crowd congestion, where the study of exit location, angle and morphology is the most common, and the study of congestion optimization at exit bottlenecks has also made good progress. The Mass Motion software based on the social force model is often used for evacuation exit studies. In addition, in this part of the research, many scholars choose to carry out crowd evacuation experiments, in order to better observe the phenomenon of exit blockage by combining experiments and simulations. Some of the typical exit evacuation experiments are shown in Fig. 12.

      Figure 12. 

      The exit evacuation experiments. Reprinted from Wang et al. & Shi et al. [97,98,100,102,103].

    • The purpose of this review is to unearth the data from the research literature in the field of crowd evacuation in China, a country with the largest population in the world, and explore the correlation of the research work of crowd evacuation at the current stage and the research hotspots in recent years, so as to provide some reference for the research of crowd evacuation around the world. By searching the Web of Science core database of articles related to the field of safety evacuation in China during 1990−2021, after screening, there were 1,380 papers. Using bibliometric methods, the number of relevant articles, year of publication, author distribution, journal distribution, keywords, etc., were analyzed in detail and VOSviewer software was used to explore the research hotspots in this field. The following conclusions were obtained from this study:

      The 1,380 retrieved documents were divided into three phases in chronological order, indicating a rising trend of the number of publications. There are 56 categories of disciplines involved in the field of safety evacuation in China and the top three disciplines are Engineering, Physics and Computer Science. Song is the scholar who has published the most articles in the field of safety evacuation in China. The literature comes from nearly 200 journals, with the greatest number of articles published in Physica A Statistical Mechanics And Its Applications. Most of the top 10 cited papers are reported before 2010, and the most cited paper is Modeling crowd evacuation of a building based on seven methodological approaches published by Zheng et al.[41].

      The analysis of keywords shows that the current research hotspots in the field of safety evacuation in China mainly focus on simulation, model and behavior. The cellular automata model has been a popular model for safety evacuation research. In the second and third stages, the keyword 'behavior' appears more frequently. In the third stage, the research on crowd path planning and exit selection behavior has increased significantly. According to the keyword analysis, the hot spots of safety evacuation research in China are mass crowd evacuation, evacuation path planning, and optimal design of evacuation exits in recent years.

      Safety evacuation is of great significance to ensure that personnel escape from dangerous situations smoothly during emergencies. With the deepening of the research in this field, it will play a very positive role in the healthy and stable development of society. Although this paper mainly focuses on the research status of one country, it also has certain reference value for related research around the world. In the field of evacuation, many Chinese scholars also refer to the work basis of foreign scholars, and Chinese scholars have extensive exchanges with scholars worldwide. However, there are still some shortcomings in the existing studies, and in future research, the following aspects should be considered:

      (1) At the research scale, most of the research in the field of safety evacuation is focused on the interior of buildings, and the research direction is rather monotonous. The research on crowd evacuation outside buildings can be increased in the future. For example, the study of crowd evacuation under outdoor toxic gas diffusion scenarios, combined with refuge areas.

      (2) Domestic research on crowd evacuation has been carried out for many years, and the creation of models has been very skillful, but there are still many difficult points that have not yet been fully understood. In different accident scenarios, the path selection of evacuation process, pedestrian evacuation behavior decisions, etc. are significantly different, so the future still establishes the need for emergency evacuation models in different disaster environments to form a unified model framework.

      (3) According to the number of publications in recent years, the number of publications in the field of safety evacuation is not continuously increasing, indicating that the research in this field is still in the exploration stage, so the field still needs to increase innovative research efforts and cultivate more outstanding talent.

      In future work, we will further investigate and analyze the research status and trend of this field globally, so as to provide more useful information for promoting the study of crowd evacuation.

      • This research was sponsored by the Major Natural Science Research Projects in Colleges and Universities of Jiangsu Province (No.19KJA460011), the National Natural Science Foundations of China (No.71774079, No.51874182), the Qinglan Project of Jiangsu Province and a project funded by the Priority Academic Program Development of Jiangsu Higher Education Institutions.

      • The authors declare that they have no conflict of interest.

      • Copyright: © 2023 by the author(s). Published by Maximum Academic Press on behalf of Nanjing Tech University. This article is an open access article distributed under Creative Commons Attribution License (CC BY 4.0), visit https://creativecommons.org/licenses/by/4.0/.
    Figure (12)  Table (11) References (108)
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    Shao X, Ye R, Wang J, Feng J, Wang Y, et al. 2023. Progress and prospects in crowd safety evacuation research in China. Emergency Management Science and Technology 3:1 doi: 10.48130/EMST-2023-0001
    Shao X, Ye R, Wang J, Feng J, Wang Y, et al. 2023. Progress and prospects in crowd safety evacuation research in China. Emergency Management Science and Technology 3:1 doi: 10.48130/EMST-2023-0001

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